{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\data\Vote20-KH_log_v60_ForReleaseR2-FPA.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}20 Nov 2023, 18:21:44
{txt}
{com}. 
. #delimit ;
{txt}delimiter now ;
{com}. use Vote20_KH_v6_Release, clear ;
{txt}
{com}. describe ;

{txt}Contains data from {res}Vote20_KH_v6_Release.dta
{txt}  obs:{res}           888                          
{txt} vars:{res}           101                          20 Nov 2023 17:21
{txt} size:{res}       341,880                          
{txt}{hline}
              storage   display    value
variable name   type    format     label      variable label
{hline}
{p 0 48}{res}{bind:TownID         }{txt}{bind: long    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}TownID{p_end}
{p 0 48}{bind:li_id          }{txt}{bind: str11   }{bind:{txt}%11s      }{space 1}{bind:         }{bind:  }{res}{res}Li-ID_Text{p_end}
{p 0 48}{bind:ID_Li          }{txt}{bind: long    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Li-ID_Number{p_end}
{p 0 48}{bind:county         }{txt}{bind: str9    }{bind:{txt}%9s       }{space 1}{bind:         }{bind:  }{res}{res}County Name{p_end}
{p 0 48}{bind:town           }{txt}{bind: str12   }{bind:{txt}%12s      }{space 1}{bind:         }{bind:  }{res}{res}Town Name{p_end}
{p 0 48}{bind:li             }{txt}{bind: str15   }{bind:{txt}%15s      }{space 1}{bind:         }{bind:  }{res}{res}Li/Neighborhood Name{p_end}
{p 0 48}{bind:DPP_2014       }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_DPP_2014{p_end}
{p 0 48}{bind:KMT_2014       }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_KMT_2014{p_end}
{p 0 48}{bind:Other_2014     }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_Other_2014{p_end}
{p 0 48}{bind:vaild_vote_2014}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All-vaild_2014{p_end}
{p 0 48}{bind:invaild_vo~2014}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All-invaild_2014{p_end}
{p 0 48}{bind:turnout_2014   }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All_2014{p_end}
{p 0 48}{bind:num_voter_2014 }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Electorate_TotalNum_2014{p_end}
{p 0 48}{bind:DPP_rate_2014  }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_DPP_2014{p_end}
{p 0 48}{bind:KMT_rate_2014  }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_KMT_2014{p_end}
{p 0 48}{bind:abstention_2014}{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_Abstention_2014{p_end}
{p 0 48}{bind:DPP_2016       }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_DPP_2016{p_end}
{p 0 48}{bind:KMT_2016       }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_KMT_2016{p_end}
{p 0 48}{bind:Other_2016     }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_Other_2016{p_end}
{p 0 48}{bind:valid_vote_2016}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All-vaild_2016{p_end}
{p 0 48}{bind:invalid_vo~2016}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All-invaild_2016{p_end}
{p 0 48}{bind:turnout_2016   }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All_2016{p_end}
{p 0 48}{bind:num_voter_2016 }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Electorate_TotalNum_2016{p_end}
{p 0 48}{bind:DPP_rate_2016  }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_DPP_2016{p_end}
{p 0 48}{bind:KMT_rate_2016  }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_KMT_2016{p_end}
{p 0 48}{bind:abstention_2016}{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_Abstention_2016{p_end}
{p 0 48}{bind:DPP_2018       }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_DPP_2018{p_end}
{p 0 48}{bind:KMT_2018       }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_KMT_2018{p_end}
{p 0 48}{bind:Other_2018     }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_Other_2018{p_end}
{p 0 48}{bind:vaild_vote_2018}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All-vaild_2018{p_end}
{p 0 48}{bind:invaild_vo~2018}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All-invaild_2018{p_end}
{p 0 48}{bind:turnout_2018   }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All_2018{p_end}
{p 0 48}{bind:num_voter_2018 }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Electorate_TotalNum_2018{p_end}
{p 0 48}{bind:DPP_rate_2018  }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_DPP_2018{p_end}
{p 0 48}{bind:KMT_rate_2018  }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_KMT_2018{p_end}
{p 0 48}{bind:abstention_2018}{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_Abstention_2018{p_end}
{p 0 48}{bind:DPP_2020       }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_DPP_2020{p_end}
{p 0 48}{bind:KMT_2020       }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_KMT_2020{p_end}
{p 0 48}{bind:Other_2020     }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_Other_2020{p_end}
{p 0 48}{bind:valid_vote_2020}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All-vaild_2020{p_end}
{p 0 48}{bind:invalid_vo~2020}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All-invaild_2020{p_end}
{p 0 48}{bind:turnout_2020   }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Vote_All_2020{p_end}
{p 0 48}{bind:num_voter_2020 }{txt}{bind: long    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Electorate_TotalNum_2020{p_end}
{p 0 48}{bind:DPP_rate_2020  }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_DPP_2020{p_end}
{p 0 48}{bind:KMT_rate_2020  }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_KMT_2020{p_end}
{p 0 48}{bind:abstention_2020}{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}VoteShare_Abstention_2020{p_end}
{p 0 48}{bind:P_CNT_2014     }{txt}{bind: long    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_All_2014{p_end}
{p 0 48}{bind:M_CNT_2014     }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Male_2014{p_end}
{p 0 48}{bind:P_DEN_2014     }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population Density_2014{p_end}
{p 0 48}{bind:A0A5_CNT_2014  }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 0-5_2014{p_end}
{p 0 48}{bind:A15A64_CNT_2014}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 15-64_2014{p_end}
{p 0 48}{bind:A65UP_CNT_2014 }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 65-_2014{p_end}
{p 0 48}{bind:college_2014   }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: College_2014{p_end}
{p 0 48}{bind:jcollege_2014  }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: Junior College_2014{p_end}
{p 0 48}{bind:highschool_2014}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: High School_2014{p_end}
{p 0 48}{bind:P_CNT_2015     }{txt}{bind: long    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_All_2015-Dec{p_end}
{p 0 48}{bind:M_CNT_2015     }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Male_2015-Dec{p_end}
{p 0 48}{bind:P_DEN_2015     }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population Density_2015-Dec{p_end}
{p 0 48}{bind:A0A5_CNT_2015  }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 0-5_2015-Dec{p_end}
{p 0 48}{bind:A15A64_CNT_2015}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 15-64_2015-Dec{p_end}
{p 0 48}{bind:A65UP_CNT_2015 }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 65-_2015-Dec{p_end}
{p 0 48}{bind:college_2015   }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: College_2015-Dec{p_end}
{p 0 48}{bind:jcollege_2015  }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: Junior College_2015-Dec{p_end}
{p 0 48}{bind:highschool_2015}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: High School_2015-Dec{p_end}
{p 0 48}{bind:P_CNT_2018     }{txt}{bind: long    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_All_2018{p_end}
{p 0 48}{bind:M_CNT_2018     }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Male_2018{p_end}
{p 0 48}{bind:P_DEN_2018     }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population Density_2018{p_end}
{p 0 48}{bind:A0A5_CNT_2018  }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 0-5_2018{p_end}
{p 0 48}{bind:A15A64_CNT_2018}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 15-64_2018{p_end}
{p 0 48}{bind:A65UP_CNT_2018 }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 65-_2018{p_end}
{p 0 48}{bind:college_2018   }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: College_2018{p_end}
{p 0 48}{bind:jcollege_2018  }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: Junior College_2018{p_end}
{p 0 48}{bind:highschool_2018}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: High School_2018{p_end}
{p 0 48}{bind:P_CNT_2020     }{txt}{bind: long    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population Density_2020-Spring{p_end}
{p 0 48}{bind:M_CNT_2020     }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Male_2020-Spring{p_end}
{p 0 48}{bind:P_DEN_2020     }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population Density_2020-Spring{p_end}
{p 0 48}{bind:A0A5_CNT_2020  }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 0-5_2020-Spring{p_end}
{p 0 48}{bind:A15A64_CNT_2020}{txt}{bind: long    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 15-64_2020-Spring{p_end}
{p 0 48}{bind:A65UP_CNT_2020 }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Age: 65-_2020-Spring{p_end}
{p 0 48}{bind:college_2020   }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: College_2020-Spring{p_end}
{p 0 48}{bind:jcollege_2020  }{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: Junior College_2020-Spring{p_end}
{p 0 48}{bind:highschool_2020}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Population_Education: High School_2020-Spring{p_end}
{p 0 48}{bind:inc_2014       }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Income_2014{p_end}
{p 0 48}{bind:inc_2015       }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Income_2015{p_end}
{p 0 48}{bind:inc_2016       }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Income_2016{p_end}
{p 0 48}{bind:inc_2017       }{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Income_2017{p_end}
{p 0 48}{bind:Price_unit~2014}{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}House Price_Unit-mean_2014{p_end}
{p 0 48}{bind:Price_un~n_2017}{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}House Price_Unit-mean_2017{p_end}
{p 0 48}{bind:Price_un~4_2017}{txt}{bind: double  }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}House Price_Unit-mean_From 2014 to 2017{p_end}
{p 0 48}{bind:temple         }{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Temple_All_Number{p_end}
{p 0 48}{bind:mazu           }{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Temple_Mazu-Temple_Number{p_end}
{p 0 48}{bind:guandi         }{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Temple_Guandi-Temple_Number{p_end}
{p 0 48}{bind:yiguandao      }{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Temple_Yiguandao-Temple_Number{p_end}
{p 0 48}{bind:urban_mazu     }{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Temple_Mazu-Temple: Urban-Type_Number{p_end}
{p 0 48}{bind:argi_mazu      }{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Temple_Mazu-Temple: Village-Type_Number{p_end}
{p 0 48}{bind:church         }{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Christian Church{p_end}
{p 0 48}{bind:anti_gay       }{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Christian Church_Join-Anti-Gay-Movement{p_end}
{p 0 48}{bind:tw_presbyteri~g}{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Christian Church_Taiwan-Presbyterian{p_end}
{p 0 48}{bind:hotel_num_2018 }{txt}{bind: byte    }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Hotel_Number_2018{p_end}
{p 0 48}{bind:hotel_capa_2018}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Hotel_Room-Number/Capacity_2018{p_end}
{p 0 48}{bind:hotel_staf~2018}{txt}{bind: int     }{bind:{txt}%10.0g    }{space 1}{bind:         }{bind:  }{res}{res}Hotel_Staff-Number_2018{p_end}
{txt}{hline}
Sorted by: 

{com}. ** --------------------------- Important!!!-----------------------------          ** ;
. **   Because this do file will run spatial regression, before running this do ** ;
. **   file, you have to check whether your system satisfies the conditions     ** ;
. **   below:                                                                                                                               ** ;
. **   1. Your STATA can run spatial regression (STATA 15 or higher).                       ** ;
. **   2. You have to put the dataset file and also the TWO GIS files           ** ;
. **      (VillageKHadj_NLSC_1041007 and VillageKHadj_NLSC_1041007_shp) in the  ** ;
. **      same folder. The two GIS files have the geographic information about  ** ;
. **      the neighborhoods in Kaohsiung, Taiwan.                                                           ** ;
. ** This is the official version for the publication:                                              ** ;
. **   The dataset used in this file is the dataset in version 6, where we add  ** ;
. **   two variables, "guandi" and "yiguandao," based on the suggestions        ** ;
. **   provided by the reviewers in the 2nd round.                                                          ** ;
. *gen CityID = round(TownID/100000) ;
. ** Merge panel data with the Stata-format shapefiles ** ;
. merge m:1 ID_Li using VillageKHadj_NLSC_1041007 ;
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}               0
{txt}{col 5}matched{col 30}{res}             888{txt}  (_merge==3)
{col 5}{hline 41}

{com}. keep if _merge==3 ;
{txt}(0 observations deleted)

{com}. drop _merge ;
{txt}
{com}. ** Generate variables  ** ;
. ** Dependent variables ** ;
. * The difference between the changes in vote-shares of 2018-2014 for DDP and KMT * ;
. gen chdppabs18 = ln(DPP_rate_2018/abstention_2018)-ln(DPP_rate_2014/abstention_2014) ;
{txt}
{com}. gen chkmtabs18 = ln(KMT_rate_2018/abstention_2018)-ln(KMT_rate_2014/abstention_2014) ;
{txt}
{com}. gen chcandabs18dk = ( ln(DPP_rate_2018/abstention_2018)-ln(DPP_rate_2014/abstention_2014) )
>                                         - ( ln(KMT_rate_2018/abstention_2018)-ln(KMT_rate_2014/abstention_2014) ) ;
{txt}
{com}. * The difference between the changes in vote-shares of 2020-2016 for DDP and KMT * ;
. gen chdppabs20 = ln(DPP_rate_2020/abstention_2020)-ln(DPP_rate_2016/abstention_2016) ;
{txt}
{com}. gen chkmtabs20 = ln(KMT_rate_2020/abstention_2020)-ln(KMT_rate_2016/abstention_2016) ;
{txt}
{com}. gen chcandabs20dk = ( ln(DPP_rate_2020/abstention_2020)-ln(DPP_rate_2016/abstention_2016) )
>                                         - ( ln(KMT_rate_2020/abstention_2020)-ln(KMT_rate_2016/abstention_2016) ) ;
{txt}
{com}. ** Key dependent variables ** ;
. * Temple_Density ;
. gen tempden    = temple / (P_CNT_2018/P_DEN_2018) ;
{txt}
{com}. * Mazu temple_Density ;
. gen mazuden    = mazu / (P_CNT_2018/P_DEN_2018) ;
{txt}
{com}. gen lnmazuden      = ln(mazuden+1) ;
{txt}
{com}. * Mazu temple deusity_Urban vs village temples ;
. gen urbanmazuden   = urban_mazu / (P_CNT_2018/P_DEN_2018) ;
{txt}
{com}. gen argimazuden    = argi_mazu / (P_CNT_2018/P_DEN_2018) ;
{txt}
{com}. gen lnurbanmazuden = ln(urbanmazuden+1) ;
{txt}
{com}. gen lnargimazuden  = ln(argimazuden+1) ;
{txt}
{com}. * Guandi temple_Density ;
. gen guanden = guandi / (P_CNT_2018/P_DEN_2018) ;
{txt}
{com}. gen lnguanden        = ln(guanden+1) ;
{txt}
{com}. gen othertempdenv1 = tempden - mazuden - guanden ;
{txt}
{com}. gen lnothertempdenv1 = ln(othertempdenv1+1) ;
{txt}
{com}. * Yiguandao temple_Density ;
. gen yiguanden = yiguandao / (P_CNT_2018/P_DEN_2018) ;
{txt}
{com}. gen lnyiguanden      = ln(yiguanden+1) ;
{txt}
{com}. gen othertempdenv2 = tempden - mazuden - guanden - yiguanden ;
{txt}
{com}. gen lnothertempdenv2 = ln(othertempdenv2+1) ;
{txt}
{com}. ** Control variables ** ;
. * Church_Density ;
. gen churchden = church / (P_CNT_2018/P_DEN_2018) ;
{txt}
{com}. gen lnchurchden = ln(churchden+1) ;
{txt}
{com}. * Average income ;
. gen inc_avg_1417 = (inc_2014 + inc_2017)/2 ;
{txt}
{com}. * Housing price (change unit) ;
. replace Price_unit_mean_2014_2017 = 10 * Price_unit_mean_2014_2017 ;
{txt}(888 real changes made)

{com}. replace Price_unit_mean_2014 = 10 * Price_unit_mean_2014 ;
{txt}(888 real changes made)

{com}. replace Price_unit_mean_2017 = 10 * Price_unit_mean_2017 ;
{txt}(888 real changes made)

{com}. * Demographic variables ;
. gen popch_1418    = P_CNT_2018 - P_CNT_2014 ;
{txt}
{com}. gen popdench_1418 = P_DEN_2018 - P_DEN_2014 ;
{txt}
{com}. gen popden_1418 = (P_DEN_2014 + P_DEN_2018)/2 ;
{txt}
{com}. gen popden_1520 = (P_DEN_2015 + P_DEN_2020)/2 ;
{txt}
{com}. gen old_1418 = ((A65UP_CNT_2018/P_CNT_2018) + (A65UP_CNT_2014/P_CNT_2014))/2 ;
{txt}
{com}. gen old_1520 = ((A65UP_CNT_2020/P_CNT_2020) + (A65UP_CNT_2015/P_CNT_2015))/2 ;
{txt}
{com}. gen old_14 = (A65UP_CNT_2014/P_CNT_2014) ;
{txt}
{com}. gen old_15 = (A65UP_CNT_2015/P_CNT_2015) ;
{txt}
{com}. gen child_1418 = ((A0A5_CNT_2018/P_CNT_2018) + (A0A5_CNT_2014/P_CNT_2014))/2 ;
{txt}
{com}. gen child_1520 = ((A0A5_CNT_2020/P_CNT_2020) + (A0A5_CNT_2015/P_CNT_2015))/2 ;
{txt}
{com}. gen child_14 = (A0A5_CNT_2014/P_CNT_2014) ;
{txt}
{com}. gen child_15 = (A0A5_CNT_2015/P_CNT_2015) ;
{txt}
{com}. * Education ;
. gen allcollege_1418 = (((college_2014+jcollege_2014)/P_CNT_2014) +
>                                                    ((college_2018+jcollege_2018)/P_CNT_2018))/2 ;
{txt}
{com}. gen allcollege_1520 = (((college_2015+jcollege_2015)/P_CNT_2015) +
>                                                    ((college_2020+jcollege_2020)/P_CNT_2020))/2 ;
{txt}
{com}. gen allcollege_14 = ((college_2014+jcollege_2014)/P_CNT_2014) ;
{txt}
{com}. gen allcollege_15 = ((college_2015+jcollege_2015)/P_CNT_2015) ;
{txt}
{com}. * City-area ;
. gen city = 0 ;
{txt}
{com}. replace city = 1 if TownID<=6401200 ;
{txt}(527 real changes made)

{com}. * Indigenous towns ;
. gen indtn = 0 ;
{txt}
{com}. replace indtn = 1 if TownID==6403600 | TownID==6403700 | TownID==6403800 ;
{txt}(14 real changes made)

{com}. ******************************************************************************** ;
. ** Descriptive statistics ** ;
.  tabstat DPP_rate_2014 DPP_rate_2016 DPP_rate_2018 DPP_rate_2020, stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  DPP_ra~4  DPP_ra~6  DPP_ra~8  DPP_ra~0
{hline 9}{c +}{hline 40}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888       888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .4718085  .4649328  .3493817  .4920732
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .0906871  .0857971  .0781145  .0840822
{txt}{ralign 8:min} {...}
{c |}{...}
 {res} .0631799  .0545709  .0379696  .1145374
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} .7037572  .6714491  .5545977  .6758574
{txt}{hline 9}{c BT}{hline 40}

{com}. tabstat KMT_rate_2014 KMT_rate_2016 KMT_rate_2018 KMT_rate_2020, stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  KMT_ra~4  KMT_ra~6  KMT_ra~8  KMT_ra~0
{hline 9}{c +}{hline 40}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888       888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .2089824  .1866899  .3975182  .2710174
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res}  .072057  .0662829  .0816388  .0740549
{txt}{ralign 8:min} {...}
{c |}{...}
 {res} .0757212  .0622328  .2123249  .1330935
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} .6407767  .6156716  .8553459  .6725404
{txt}{hline 9}{c BT}{hline 40}

{com}. tabstat abstention_2014 abstention_2016 abstention_2018 abstention_2020, stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  abs~2014  abs~2016  abs~2018  abs~2020
{hline 9}{c +}{hline 40}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888       888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .3192091  .3483773  .2531001  .2369093
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .0701844   .050074  .0514381   .041258
{txt}{ralign 8:min} {...}
{c |}{...}
 {res} .0842105  .2356115  .0614525  .1623672
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} .6226979  .6227088  .5658263  .5159444
{txt}{hline 9}{c BT}{hline 40}

{com}. tabstat chdppabs18 chkmtabs18              , stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  chdpp~18  chkmt~18
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res}-.0890482  .8968995
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .3038052  .2642422
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}-1.967112 -.2255752
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 1.201174  2.068512
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat chdppabs18 chkmtabs18 if mazuden>0 , stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  chdpp~18  chkmt~18
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      144       144
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res}-.1516649  .8858039
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .3374532  .3565985
{txt}{ralign 8:min} {...}
{c |}{...}
 {res} -1.60979 -.2255752
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} .7532597  1.795384
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat chdppabs18 chkmtabs18 if mazuden==0, stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  chdpp~18  chkmt~18
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      744       744
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res}-.0769289  .8990471
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .2955708  .2425982
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}-1.967112 -.1025156
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 1.201174  2.068512
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat chdppabs20 chkmtabs20              , stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  chdpp~20  chkmt~20
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res}  .450272  .7802972
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .1467269  .1470399
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}-.3840132  .0718751
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 1.271392  1.364011
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat chdppabs20 chkmtabs20 if mazuden>0 , stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  chdpp~20  chkmt~20
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      144       144
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .3798654  .8003895
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .1621324  .1453724
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}-.3840132  .4063307
{txt}{ralign 8:max} {...}
{c |}{...}
 {res}   .68031  1.281608
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat chdppabs20 chkmtabs20 if mazuden==0, stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  chdpp~20  chkmt~20
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      744       744
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .4638991  .7764084
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .1396256  .1471404
{txt}{ralign 8:min} {...}
{c |}{...}
 {res} .0398826  .0718751
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 1.271392  1.364011
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat chcandabs18dk              , stat(n mean sd min max) ;

{txt}{ralign 12:variable} {...}
{c |}         N      mean        sd       min       max
{hline 13}{c +}{hline 50}
{ralign 12:chcandabs1~k} {...}
{c |}{...}
 {res}      888 -.9859477  .2227917 -2.657926 -.1717746
{txt}{hline 13}{c BT}{hline 50}

{com}. tabstat chcandabs18dk if mazuden>0 , stat(n mean sd min max) ;

{txt}{ralign 12:variable} {...}
{c |}         N      mean        sd       min       max
{hline 13}{c +}{hline 50}
{ralign 12:chcandabs1~k} {...}
{c |}{...}
 {res}      144 -1.037469  .2305703 -1.680891 -.4176699
{txt}{hline 13}{c BT}{hline 50}

{com}. tabstat chcandabs18dk if mazuden==0, stat(n mean sd min max) ;

{txt}{ralign 12:variable} {...}
{c |}         N      mean        sd       min       max
{hline 13}{c +}{hline 50}
{ralign 12:chcandabs1~k} {...}
{c |}{...}
 {res}      744 -.9759759  .2200232 -2.657926 -.1717746
{txt}{hline 13}{c BT}{hline 50}

{com}. tabstat chcandabs20dk              , stat(n mean sd min max) ;

{txt}{ralign 12:variable} {...}
{c |}         N      mean        sd       min       max
{hline 13}{c +}{hline 50}
{ralign 12:chcandabs2~k} {...}
{c |}{...}
 {res}      888 -.3300252  .1597331 -1.356055  .7488173
{txt}{hline 13}{c BT}{hline 50}

{com}. tabstat chcandabs20dk if mazuden>0 , stat(n mean sd min max) ;

{txt}{ralign 12:variable} {...}
{c |}         N      mean        sd       min       max
{hline 13}{c +}{hline 50}
{ralign 12:chcandabs2~k} {...}
{c |}{...}
 {res}      144 -.4205241  .1703061 -1.356055 -.1049872
{txt}{hline 13}{c BT}{hline 50}

{com}. tabstat chcandabs20dk if mazuden==0, stat(n mean sd min max) ;

{txt}{ralign 12:variable} {...}
{c |}         N      mean        sd       min       max
{hline 13}{c +}{hline 50}
{ralign 12:chcandabs2~k} {...}
{c |}{...}
 {res}      744 -.3125093   .151601 -.9371364  .7488173
{txt}{hline 13}{c BT}{hline 50}

{com}. tabstat temple mazu urban_mazu argi_mazu, stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
    temple      mazu  urban_~u  argi_m~u
{hline 9}{c +}{hline 40}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888       888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} 1.679054  .1835586  .0225225   .161036
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} 2.240231  .4493261   .148459  .4299548
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0         0         0         0
{txt}{ralign 8:max} {...}
{c |}{...}
 {res}       18         3         1         3
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0         0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res}        1         0         0         0
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res}        2         0         0         0
{txt}{hline 9}{c BT}{hline 40}

{com}. tabstat tempden mazuden urbanmazuden argimazuden, stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
   tempden   mazuden  urbanm~n  argima~n
{hline 9}{c +}{hline 40}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888       888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res}  3.61678  .4290899  .1782159  .2508741
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} 7.363577  2.155792  1.406489  1.660886
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0         0         0         0
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 66.16238   27.8257  16.23508   27.8257
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0         0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res} .6853323         0         0         0
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res} 3.313505         0         0         0
{txt}{hline 9}{c BT}{hline 40}

{com}. tabstat lnmazuden lnurbanmazuden lnargimazuden, stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
  lnmazu~n  lnurba~n  lnargi~n
{hline 9}{c +}{hline 30}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .1313387  .0433623  .0880383
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .4566188  .3114121  .3450455
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 3.361267  2.846947  3.361267
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res}        0         0         0
{txt}{hline 9}{c BT}{hline 30}

{com}. tabstat mazuden urbanmazuden argimazuden if city==1, stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
   mazuden  urbanm~n  argima~n
{hline 9}{c +}{hline 30}
{ralign 8:N} {...}
{c |}{...}
 {res}      527       527       527
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res}  .551154  .2997244  .2514297
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} 2.628828  1.816404  1.939695
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:max} {...}
{c |}{...}
 {res}  27.8257  16.23508   27.8257
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res}        0         0         0
{txt}{hline 9}{c BT}{hline 30}

{com}. tabstat mazuden urbanmazuden argimazuden if city==0, stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
   mazuden  urbanm~n  argima~n
{hline 9}{c +}{hline 30}
{ralign 8:N} {...}
{c |}{...}
 {res}      361       361       361
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .2508967  .0008337  .2500629
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} 1.140073  .0158407  1.139925
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 13.56779  .3009735  13.56779
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res} .0974216         0  .0974216
{txt}{hline 9}{c BT}{hline 30}

{com}. tabstat guanden   othertempdenv1  , stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
   guanden  othert~1
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .3482667  2.839423
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} 2.510165  6.213435
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0         0
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 39.92015  66.16238
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res}        0  .4522842
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res}        0  2.526595
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat lnguanden lnothertempdenv1, stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
  lnguan~n  lnothe~1
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .0813712  .7471013
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res}  .400859  .9434133
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0         0
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 3.711623  4.207113
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res}        0  .3731339
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res}        0  1.260332
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat yiguanden   othertempdenv2  , stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
  yiguan~n  othert~2
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .0217345  2.817689
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .2645376  6.208777
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0 -.4154444
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 6.097821  66.16238
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res}        0  .4392397
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res}        0  2.509312
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat lnyiguanden lnothertempdenv2, stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
  lnyigu~n  lnothe~2
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .0111902  .7408437
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .1091463  .9418865
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0 -.5369034
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 1.959788  4.207113
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res}        0  .3641121
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res}        0  1.255414
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat church               , stat(n mean sd min max p25 p50 p75) ;

{txt}{ralign 12:variable} {...}
{c |}         N      mean        sd       min       max       p25       p50
{hline 13}{c +}{hline 70}
{ralign 12:church} {...}
{c |}{...}
 {res}      888  .6193694  1.072011         0        13         0         0
{txt}{hline 13}{c BT}{hline 70}

{ralign 12:variable} {...}
{c |}       p75
{hline 13}{c +}{hline 10}
{ralign 12:church} {...}
{c |}{...}
 {res}        1
{txt}{hline 13}{c BT}{hline 10}

{com}. tabstat churchden lnchurchden, stat(n mean sd min max p25 p50 p75) ;

{txt}   stats {...}
{c |}{...}
  church~n  lnchur~n
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} 2.904267  .6456196
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} 6.546062   1.02437
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0         0
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} 57.84694   4.07494
{txt}{ralign 8:p25} {...}
{c |}{...}
 {res}        0         0
{txt}{ralign 8:p50} {...}
{c |}{...}
 {res}        0         0
{txt}{ralign 8:p75} {...}
{c |}{...}
 {res} 2.370072   1.21493
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat popdench_1418 popden_1418 popden_1520, stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  popdenc~  p~n_1418  pop~1520
{hline 9}{c +}{hline 30}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res}-374.1223  12901.68  12807.07
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} 868.0377   12999.9  12892.72
{txt}{ralign 8:min} {...}
{c |}{...}
 {res} -6560.65      .695       .68
{txt}{ralign 8:max} {...}
{c |}{...}
 {res}  3511.95   96413.9  95807.73
{txt}{hline 9}{c BT}{hline 30}

{com}. tabstat old_1418    old_1520  , stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  old_1418  old_1520
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .1579889  .1680838
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .0479172  .0486499
{txt}{ralign 8:min} {...}
{c |}{...}
 {res} .0337406  .0415595
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} .3438644  .3453946
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat child_1418  child_1520, stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  chi~1418  chi~1520
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .0416211  .0410831
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .0126176  .0124753
{txt}{ralign 8:min} {...}
{c |}{...}
 {res} .0092077  .0051813
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} .1367242   .129936
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat allcollege_1418 allcollege_1520, stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  all~1418  all~1520
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .2840721  .2926497
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .0926229  .0933351
{txt}{ralign 8:min} {...}
{c |}{...}
 {res} .0531807  .0563598
{txt}{ralign 8:max} {...}
{c |}{...}
 {res} .6048958  .6154115
{txt}{hline 9}{c BT}{hline 20}

{com}. tabstat inc_avg_1417, stat(n mean sd min max) ;

{txt}{ralign 12:variable} {...}
{c |}         N      mean        sd       min       max
{hline 13}{c +}{hline 50}
{ralign 12:inc_avg_1417} {...}
{c |}{...}
 {res}      888  813.4844  192.5417       484      2194
{txt}{hline 13}{c BT}{hline 50}

{com}. tabstat Price_unit_mean_2014_2017, stat(n mean sd min max) ;

{txt}{ralign 12:variable} {...}
{c |}         N      mean        sd       min       max
{hline 13}{c +}{hline 50}
{ralign 12:Price~4_2017} {...}
{c |}{...}
 {res}      888  39.76195  18.74184  .2177948  68.62316
{txt}{hline 13}{c BT}{hline 50}

{com}. tabstat hotel_num_2018 hotel_capa_2018 hotel_staff_2018, stat(n mean sd min max) ;

{txt}   stats {...}
{c |}{...}
  h~m_2018  h~a_2018  h~f_2018
{hline 9}{c +}{hline 30}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .4211712  54.81194  6.666667
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} 1.204315  180.0703   23.7878
{txt}{ralign 8:min} {...}
{c |}{...}
 {res}        0         0         0
{txt}{ralign 8:max} {...}
{c |}{...}
 {res}       13      1744       285
{txt}{hline 9}{c BT}{hline 30}

{com}. tabstat city indtn, stat(n mean sd) ;

{txt}   stats {...}
{c |}{...}
      city     indtn
{hline 9}{c +}{hline 20}
{ralign 8:N} {...}
{c |}{...}
 {res}      888       888
{txt}{ralign 8:mean} {...}
{c |}{...}
 {res} .5934685  .0157658
{txt}{ralign 8:sd} {...}
{c |}{...}
 {res} .4914628  .1246383
{txt}{hline 9}{c BT}{hline 20}

{com}. ******************************************************************************** ;
. ** Create spatial weighting W ** ;
. spmatrix create idistance  Wd, vtruncate(.5) ;
{res}{p 2 2 2}{txt} weighting matrix in {inp}Wd {txt}contains 64 islands
{p_end}

{com}. ** Main regression                      ** ;
. ** Spatial regression       ** ;
. ** Model_distance weighting ** ;
. ** The four regression commands below are those for the official  ** ;
. **   article published in Foreign Policy Analysis.                                ** ;
. ** Temple types: Mazu, Guandi, and the others             ;
. *    1-1-2018: Mazu, Guandi temples and Other temples ;
. spregress chcandabs18dk lnmazuden lnguanden lnothertempdenv1 
>                                     lnchurchden  
>                                         popden_1418   
>                                     child_1418 old_1418  
>                                         allcollege_1418  
>                                         inc_avg_1417 Price_unit_mean_2014_2017  
>                                         hotel_num_2018  
>                                         city indtn,
>                                                 ml   
>                                             ivarlag(Wd: lnmazuden lnguanden lnothertempdenv1) ;
{res}{txt}{col 3}(888 observations)
{col 3}(888 observations (places) used)
{col 3}(weighting matrix defines 888 places)
{res}{txt}
Optimizing unconcentrated log likelihood:

Iteration 0:{space 3}log likelihood = {res: 327.82851}  
Iteration 1:{space 3}log likelihood = {res: 327.82851}  (backed up)
{res}
{txt}Spatial autoregressive model{col 49}Number of obs{col 67}= {res}       888
{txt}Maximum likelihood estimates{col 49}Wald chi2({res}16{txt}){col 67}= {res}    685.47
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} 327.82851{txt}{col 49}Pseudo R2{col 67}= {res}    0.4356

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           chcandabs18dk{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}chcandabs18dk            {txt}{c |}
{space 15}lnmazuden {c |}{col 26}{res}{space 2}-.0181377{col 38}{space 2} .0124581{col 49}{space 1}   -1.46{col 58}{space 3}0.145{col 66}{space 4}-.0425551{col 79}{space 3} .0062797
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .0027204{col 38}{space 2} .0144228{col 49}{space 1}    0.19{col 58}{space 3}0.850{col 66}{space 4}-.0255478{col 79}{space 3} .0309886
{txt}{space 8}lnothertempdenv1 {c |}{col 26}{res}{space 2} .0024024{col 38}{space 2} .0062098{col 49}{space 1}    0.39{col 58}{space 3}0.699{col 66}{space 4}-.0097686{col 79}{space 3} .0145733
{txt}{space 13}lnchurchden {c |}{col 26}{res}{space 2}-.0011489{col 38}{space 2} .0061896{col 49}{space 1}   -0.19{col 58}{space 3}0.853{col 66}{space 4}-.0132803{col 79}{space 3} .0109826
{txt}{space 13}popden_1418 {c |}{col 26}{res}{space 2} 7.46e-07{col 38}{space 2} 6.52e-07{col 49}{space 1}    1.14{col 58}{space 3}0.253{col 66}{space 4}-5.32e-07{col 79}{space 3} 2.02e-06
{txt}{space 14}child_1418 {c |}{col 26}{res}{space 2}-2.727207{col 38}{space 2} .7204777{col 49}{space 1}   -3.79{col 58}{space 3}0.000{col 66}{space 4}-4.139317{col 79}{space 3}-1.315096
{txt}{space 16}old_1418 {c |}{col 26}{res}{space 2} .9219702{col 38}{space 2} .1868697{col 49}{space 1}    4.93{col 58}{space 3}0.000{col 66}{space 4} .5557122{col 79}{space 3} 1.288228
{txt}{space 9}allcollege_1418 {c |}{col 26}{res}{space 2} 1.235223{col 38}{space 2} .1203918{col 49}{space 1}   10.26{col 58}{space 3}0.000{col 66}{space 4} .9992598{col 79}{space 3} 1.471187
{txt}{space 12}inc_avg_1417 {c |}{col 26}{res}{space 2}-.0000599{col 38}{space 2} .0000433{col 49}{space 1}   -1.38{col 58}{space 3}0.167{col 66}{space 4}-.0001449{col 79}{space 3}  .000025
{txt}Price_unit_mean_201~2017 {c |}{col 26}{res}{space 2} .0003631{col 38}{space 2} .0006793{col 49}{space 1}    0.53{col 58}{space 3}0.593{col 66}{space 4}-.0009683{col 79}{space 3} .0016945
{txt}{space 10}hotel_num_2018 {c |}{col 26}{res}{space 2}-.0129873{col 38}{space 2} .0050175{col 49}{space 1}   -2.59{col 58}{space 3}0.010{col 66}{space 4}-.0228215{col 79}{space 3}-.0031531
{txt}{space 20}city {c |}{col 26}{res}{space 2}-.0937517{col 38}{space 2} .0232499{col 49}{space 1}   -4.03{col 58}{space 3}0.000{col 66}{space 4}-.1393207{col 79}{space 3}-.0481827
{txt}{space 19}indtn {c |}{col 26}{res}{space 2}-.5163658{col 38}{space 2}   .05266{col 49}{space 1}   -9.81{col 58}{space 3}0.000{col 66}{space 4}-.6195775{col 79}{space 3} -.413154
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-1.271228{col 38}{space 2} .0583284{col 49}{space 1}  -21.79{col 58}{space 3}0.000{col 66}{space 4}-1.385549{col 79}{space 3}-1.156906
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Wd                       {txt}{c |}
{space 15}lnmazuden {c |}{col 26}{res}{space 2}-.2900358{col 38}{space 2} .1483707{col 49}{space 1}   -1.95{col 58}{space 3}0.051{col 66}{space 4}-.5808371{col 79}{space 3} .0007656
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .2623249{col 38}{space 2} .2055452{col 49}{space 1}    1.28{col 58}{space 3}0.202{col 66}{space 4}-.1405362{col 79}{space 3}  .665186
{txt}{space 8}lnothertempdenv1 {c |}{col 26}{res}{space 2} .0014807{col 38}{space 2} .0435241{col 49}{space 1}    0.03{col 58}{space 3}0.973{col 66}{space 4}-.0838249{col 79}{space 3} .0867864
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.chcandabs18dk){c |}{col 26}{res}{space 2}  .027981{col 38}{space 2} .0013279{col 66}{space 4} .0254957{col 79}{space 3} .0307086
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Wald test of spatial terms:{col 38}chi2({res}3{txt}) = {res}6.78    {col 59}{txt}Prob > chi2 = {res}0.0794
{txt}
{com}. estat impact lnmazuden lnguanden lnothertempdenv1 ;
{res}
{txt}progress{col 12}:{txt} 33% {txt} 67% {txt}100% 

Average impacts{col 49}Number of obs{col 67}={col 69}{res}       888

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-Method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}direct           {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.0181377{col 30}{space 2} .0124581{col 41}{space 1}   -1.46{col 50}{space 3}0.145{col 58}{space 4}-.0425551{col 71}{space 3} .0062797
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0027204{col 30}{space 2} .0144228{col 41}{space 1}    0.19{col 50}{space 3}0.850{col 58}{space 4}-.0255478{col 71}{space 3} .0309886
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2} .0024024{col 30}{space 2} .0062098{col 41}{space 1}    0.39{col 50}{space 3}0.699{col 58}{space 4}-.0097686{col 71}{space 3} .0145733
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}indirect         {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.1026205{col 30}{space 2} .0524965{col 41}{space 1}   -1.95{col 50}{space 3}0.051{col 58}{space 4}-.2055118{col 71}{space 3} .0002709
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0928158{col 30}{space 2}  .072726{col 41}{space 1}    1.28{col 50}{space 3}0.202{col 58}{space 4}-.0497245{col 71}{space 3} .2353561
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2} .0005239{col 30}{space 2} .0153997{col 41}{space 1}    0.03{col 50}{space 3}0.973{col 58}{space 4}-.0296589{col 71}{space 3} .0307068
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}total            {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.1207581{col 30}{space 2} .0547081{col 41}{space 1}   -2.21{col 50}{space 3}0.027{col 58}{space 4}-.2279841{col 71}{space 3}-.0135321
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0955362{col 30}{space 2}  .076062{col 41}{space 1}    1.26{col 50}{space 3}0.209{col 58}{space 4}-.0535426{col 71}{space 3}  .244615
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2} .0029263{col 30}{space 2} .0162489{col 41}{space 1}    0.18{col 50}{space 3}0.857{col 58}{space 4} -.028921{col 71}{space 3} .0347736
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *    1-1-2020: Mazu, Guandi temples and Other temples ;
. spregress chcandabs20dk lnmazuden lnguanden lnothertempdenv1 
>                                                 lnchurchden
>                                             popden_1520 
>                                     child_1520 old_1520 
>                                         allcollege_1520
>                                             inc_avg_1417 Price_unit_mean_2014_2017 
>                                             hotel_num_2018      
>                                                 city indtn,
>                                                 ml   
>                                             ivarlag(Wd: lnmazuden lnguanden lnothertempdenv1) ;
{res}{txt}{col 3}(888 observations)
{col 3}(888 observations (places) used)
{col 3}(weighting matrix defines 888 places)
{res}{txt}
Optimizing unconcentrated log likelihood:

Iteration 0:{space 3}log likelihood = {res: 528.48226}  
Iteration 1:{space 3}log likelihood = {res: 528.48226}  (backed up)
{res}
{txt}Spatial autoregressive model{col 49}Number of obs{col 67}= {res}       888
{txt}Maximum likelihood estimates{col 49}Wald chi2({res}16{txt}){col 67}= {res}    382.92
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} 528.48226{txt}{col 49}Pseudo R2{col 67}= {res}    0.3013

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           chcandabs20dk{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}chcandabs20dk            {txt}{c |}
{space 15}lnmazuden {c |}{col 26}{res}{space 2}-.0301478{col 38}{space 2} .0099365{col 49}{space 1}   -3.03{col 58}{space 3}0.002{col 66}{space 4} -.049623{col 79}{space 3}-.0106726
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2}-.0146693{col 38}{space 2} .0115061{col 49}{space 1}   -1.27{col 58}{space 3}0.202{col 66}{space 4}-.0372208{col 79}{space 3} .0078823
{txt}{space 8}lnothertempdenv1 {c |}{col 26}{res}{space 2}-.0031872{col 38}{space 2} .0049541{col 49}{space 1}   -0.64{col 58}{space 3}0.520{col 66}{space 4} -.012897{col 79}{space 3} .0065226
{txt}{space 13}lnchurchden {c |}{col 26}{res}{space 2} .0089442{col 38}{space 2} .0049307{col 49}{space 1}    1.81{col 58}{space 3}0.070{col 66}{space 4}-.0007198{col 79}{space 3} .0186082
{txt}{space 13}popden_1520 {c |}{col 26}{res}{space 2} 4.68e-07{col 38}{space 2} 5.23e-07{col 49}{space 1}    0.89{col 58}{space 3}0.371{col 66}{space 4}-5.57e-07{col 79}{space 3} 1.49e-06
{txt}{space 14}child_1520 {c |}{col 26}{res}{space 2}  1.16513{col 38}{space 2} .5972311{col 49}{space 1}    1.95{col 58}{space 3}0.051{col 66}{space 4}-.0054218{col 79}{space 3} 2.335681
{txt}{space 16}old_1520 {c |}{col 26}{res}{space 2} .5650656{col 38}{space 2} .1519595{col 49}{space 1}    3.72{col 58}{space 3}0.000{col 66}{space 4} .2672305{col 79}{space 3} .8629008
{txt}{space 9}allcollege_1520 {c |}{col 26}{res}{space 2} 1.001294{col 38}{space 2} .0957247{col 49}{space 1}   10.46{col 58}{space 3}0.000{col 66}{space 4} .8136767{col 79}{space 3} 1.188911
{txt}{space 12}inc_avg_1417 {c |}{col 26}{res}{space 2} -.000134{col 38}{space 2} .0000345{col 49}{space 1}   -3.88{col 58}{space 3}0.000{col 66}{space 4}-.0002016{col 79}{space 3}-.0000664
{txt}Price_unit_mean_201~2017 {c |}{col 26}{res}{space 2} .0001042{col 38}{space 2} .0005433{col 49}{space 1}    0.19{col 58}{space 3}0.848{col 66}{space 4}-.0009608{col 79}{space 3} .0011691
{txt}{space 10}hotel_num_2018 {c |}{col 26}{res}{space 2}-.0093317{col 38}{space 2} .0040012{col 49}{space 1}   -2.33{col 58}{space 3}0.020{col 66}{space 4}-.0171739{col 79}{space 3}-.0014896
{txt}{space 20}city {c |}{col 26}{res}{space 2} .0380604{col 38}{space 2} .0185266{col 49}{space 1}    2.05{col 58}{space 3}0.040{col 66}{space 4}  .001749{col 79}{space 3} .0743718
{txt}{space 19}indtn {c |}{col 26}{res}{space 2} .1204191{col 38}{space 2} .0414359{col 49}{space 1}    2.91{col 58}{space 3}0.004{col 66}{space 4} .0392062{col 79}{space 3} .2016321
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-.6637393{col 38}{space 2} .0481439{col 49}{space 1}  -13.79{col 58}{space 3}0.000{col 66}{space 4}-.7580997{col 79}{space 3}-.5693789
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Wd                       {txt}{c |}
{space 15}lnmazuden {c |}{col 26}{res}{space 2}-.2522098{col 38}{space 2} .1182265{col 49}{space 1}   -2.13{col 58}{space 3}0.033{col 66}{space 4}-.4839296{col 79}{space 3}-.0204901
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .0299829{col 38}{space 2} .1638563{col 49}{space 1}    0.18{col 58}{space 3}0.855{col 66}{space 4}-.2911695{col 79}{space 3} .3511353
{txt}{space 8}lnothertempdenv1 {c |}{col 26}{res}{space 2}-.0421567{col 38}{space 2} .0347132{col 49}{space 1}   -1.21{col 58}{space 3}0.225{col 66}{space 4}-.1101933{col 79}{space 3} .0258798
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.chcandabs20dk){c |}{col 26}{res}{space 2} .0178072{col 38}{space 2} .0008451{col 66}{space 4} .0162255{col 79}{space 3}  .019543
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Wald test of spatial terms:{col 38}chi2({res}3{txt}) = {res}10.07   {col 59}{txt}Prob > chi2 = {res}0.0180
{txt}
{com}. estat impact lnmazuden lnguanden lnothertempdenv1 ;
{res}
{txt}progress{col 12}:{txt} 33% {txt} 67% {txt}100% 

Average impacts{col 49}Number of obs{col 67}={col 69}{res}       888

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-Method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}direct           {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.0301478{col 30}{space 2} .0099365{col 41}{space 1}   -3.03{col 50}{space 3}0.002{col 58}{space 4} -.049623{col 71}{space 3}-.0106726
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2}-.0146693{col 30}{space 2} .0115061{col 41}{space 1}   -1.27{col 50}{space 3}0.202{col 58}{space 4}-.0372208{col 71}{space 3} .0078823
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2}-.0031872{col 30}{space 2} .0049541{col 41}{space 1}   -0.64{col 50}{space 3}0.520{col 58}{space 4} -.012897{col 71}{space 3} .0065226
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}indirect         {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.0892369{col 30}{space 2} .0418309{col 41}{space 1}   -2.13{col 50}{space 3}0.033{col 58}{space 4} -.171224{col 71}{space 3}-.0072498
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0106085{col 30}{space 2} .0579756{col 41}{space 1}    0.18{col 50}{space 3}0.855{col 58}{space 4}-.1030216{col 71}{space 3} .1242387
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2}-.0149159{col 30}{space 2} .0122822{col 41}{space 1}   -1.21{col 50}{space 3}0.225{col 58}{space 4}-.0389886{col 71}{space 3} .0091568
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}total            {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.1193847{col 30}{space 2} .0435863{col 41}{space 1}   -2.74{col 50}{space 3}0.006{col 58}{space 4}-.2048123{col 71}{space 3}-.0339571
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2}-.0040607{col 30}{space 2} .0606224{col 41}{space 1}   -0.07{col 50}{space 3}0.947{col 58}{space 4}-.1228784{col 71}{space 3}  .114757
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2}-.0181031{col 30}{space 2} .0129534{col 41}{space 1}   -1.40{col 50}{space 3}0.162{col 58}{space 4}-.0434912{col 71}{space 3} .0072851
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *    1-2-2018: Other temples, Guandi temples and Mazu temples_Urban vs village temples ;
. spregress chcandabs18dk lnurbanmazuden lnargimazuden lnguanden lnothertempdenv1
>                                     lnchurchden  
>                                         popden_1418   
>                                     child_1418 old_1418  
>                                         allcollege_1418  
>                                         inc_avg_1417 Price_unit_mean_2014_2017  
>                                         hotel_num_2018  
>                                         city indtn,
>                                                 ml   
>                                             ivarlag(Wd: lnurbanmazuden lnargimazuden lnguanden lnothertempdenv1) ;
{res}{txt}{col 3}(888 observations)
{col 3}(888 observations (places) used)
{col 3}(weighting matrix defines 888 places)
{res}{txt}
Optimizing unconcentrated log likelihood:

Iteration 0:{space 3}log likelihood = {res: 338.32517}  
Iteration 1:{space 3}log likelihood = {res: 338.32517}  (backed up)
{res}
{txt}Spatial autoregressive model{col 49}Number of obs{col 67}= {res}       888
{txt}Maximum likelihood estimates{col 49}Wald chi2({res}18{txt}){col 67}= {res}    723.11
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} 338.32517{txt}{col 49}Pseudo R2{col 67}= {res}    0.4488

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           chcandabs18dk{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}chcandabs18dk            {txt}{c |}
{space 10}lnurbanmazuden {c |}{col 26}{res}{space 2}-.0359077{col 38}{space 2} .0181307{col 49}{space 1}   -1.98{col 58}{space 3}0.048{col 66}{space 4}-.0714433{col 79}{space 3}-.0003722
{txt}{space 11}lnargimazuden {c |}{col 26}{res}{space 2}-.0024016{col 38}{space 2} .0163071{col 49}{space 1}   -0.15{col 58}{space 3}0.883{col 66}{space 4}-.0343629{col 79}{space 3} .0295598
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .0035058{col 38}{space 2} .0142607{col 49}{space 1}    0.25{col 58}{space 3}0.806{col 66}{space 4}-.0244447{col 79}{space 3} .0314562
{txt}{space 8}lnothertempdenv1 {c |}{col 26}{res}{space 2} .0002613{col 38}{space 2} .0061594{col 49}{space 1}    0.04{col 58}{space 3}0.966{col 66}{space 4}-.0118108{col 79}{space 3} .0123334
{txt}{space 13}lnchurchden {c |}{col 26}{res}{space 2}-.0001952{col 38}{space 2}  .006125{col 49}{space 1}   -0.03{col 58}{space 3}0.975{col 66}{space 4}-.0122001{col 79}{space 3} .0118096
{txt}{space 13}popden_1418 {c |}{col 26}{res}{space 2} 8.31e-07{col 38}{space 2} 6.45e-07{col 49}{space 1}    1.29{col 58}{space 3}0.197{col 66}{space 4}-4.32e-07{col 79}{space 3} 2.09e-06
{txt}{space 14}child_1418 {c |}{col 26}{res}{space 2}-2.656279{col 38}{space 2} .7130583{col 49}{space 1}   -3.73{col 58}{space 3}0.000{col 66}{space 4}-4.053848{col 79}{space 3} -1.25871
{txt}{space 16}old_1418 {c |}{col 26}{res}{space 2} .9582961{col 38}{space 2} .1849789{col 49}{space 1}    5.18{col 58}{space 3}0.000{col 66}{space 4} .5957441{col 79}{space 3} 1.320848
{txt}{space 9}allcollege_1418 {c |}{col 26}{res}{space 2} 1.225598{col 38}{space 2} .1190558{col 49}{space 1}   10.29{col 58}{space 3}0.000{col 66}{space 4} .9922527{col 79}{space 3} 1.458943
{txt}{space 12}inc_avg_1417 {c |}{col 26}{res}{space 2}-.0000495{col 38}{space 2} .0000429{col 49}{space 1}   -1.15{col 58}{space 3}0.248{col 66}{space 4}-.0001336{col 79}{space 3} .0000346
{txt}Price_unit_mean_201~2017 {c |}{col 26}{res}{space 2} .0003454{col 38}{space 2} .0006714{col 49}{space 1}    0.51{col 58}{space 3}0.607{col 66}{space 4}-.0009704{col 79}{space 3} .0016613
{txt}{space 10}hotel_num_2018 {c |}{col 26}{res}{space 2}-.0127529{col 38}{space 2} .0049592{col 49}{space 1}   -2.57{col 58}{space 3}0.010{col 66}{space 4}-.0224728{col 79}{space 3} -.003033
{txt}{space 20}city {c |}{col 26}{res}{space 2}-.0856722{col 38}{space 2} .0230616{col 49}{space 1}   -3.71{col 58}{space 3}0.000{col 66}{space 4}-.1308722{col 79}{space 3}-.0404723
{txt}{space 19}indtn {c |}{col 26}{res}{space 2}-.5097005{col 38}{space 2} .0520613{col 49}{space 1}   -9.79{col 58}{space 3}0.000{col 66}{space 4}-.6117388{col 79}{space 3}-.4076621
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-1.291857{col 38}{space 2} .0578485{col 49}{space 1}  -22.33{col 58}{space 3}0.000{col 66}{space 4}-1.405238{col 79}{space 3}-1.178476
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Wd                       {txt}{c |}
{space 10}lnurbanmazuden {c |}{col 26}{res}{space 2}-.8488818{col 38}{space 2} .1946005{col 49}{space 1}   -4.36{col 58}{space 3}0.000{col 66}{space 4}-1.230292{col 79}{space 3}-.4674717
{txt}{space 11}lnargimazuden {c |}{col 26}{res}{space 2} .3881303{col 38}{space 2} .2119545{col 49}{space 1}    1.83{col 58}{space 3}0.067{col 66}{space 4}-.0272928{col 79}{space 3} .8035535
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .2929898{col 38}{space 2} .2032866{col 49}{space 1}    1.44{col 58}{space 3}0.150{col 66}{space 4}-.1054446{col 79}{space 3} .6914241
{txt}{space 8}lnothertempdenv1 {c |}{col 26}{res}{space 2}-.0023613{col 38}{space 2} .0430321{col 49}{space 1}   -0.05{col 58}{space 3}0.956{col 66}{space 4}-.0867028{col 79}{space 3} .0819801
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.chcandabs18dk){c |}{col 26}{res}{space 2} .0273273{col 38}{space 2} .0012969{col 66}{space 4}    .0249{col 79}{space 3} .0299911
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Wald test of spatial terms:{col 38}chi2({res}4{txt}) = {res}26.32   {col 59}{txt}Prob > chi2 = {res}0.0000
{txt}
{com}. estat impact lnurbanmazuden lnargimazuden lnguanden lnothertempdenv1 ;
{res}
{txt}progress{col 12}:{txt} 25% {txt} 50% {txt} 75% {txt}100% 

Average impacts{col 49}Number of obs{col 67}={col 69}{res}       888

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-Method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}direct           {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.0359077{col 30}{space 2} .0181307{col 41}{space 1}   -1.98{col 50}{space 3}0.048{col 58}{space 4}-.0714433{col 71}{space 3}-.0003722
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2}-.0024016{col 30}{space 2} .0163071{col 41}{space 1}   -0.15{col 50}{space 3}0.883{col 58}{space 4}-.0343629{col 71}{space 3} .0295598
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0035058{col 30}{space 2} .0142607{col 41}{space 1}    0.25{col 50}{space 3}0.806{col 58}{space 4}-.0244447{col 71}{space 3} .0314562
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2} .0002613{col 30}{space 2} .0061594{col 41}{space 1}    0.04{col 50}{space 3}0.966{col 58}{space 4}-.0118108{col 71}{space 3} .0123334
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}indirect         {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.3003514{col 30}{space 2} .0688536{col 41}{space 1}   -4.36{col 50}{space 3}0.000{col 58}{space 4}-.4353019{col 71}{space 3}-.1654009
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2} .1373283{col 30}{space 2} .0749937{col 41}{space 1}    1.83{col 50}{space 3}0.067{col 58}{space 4}-.0096567{col 71}{space 3} .2843133
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .1036657{col 30}{space 2} .0719269{col 41}{space 1}    1.44{col 50}{space 3}0.150{col 58}{space 4}-.0373084{col 71}{space 3} .2446397
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2}-.0008355{col 30}{space 2} .0152256{col 41}{space 1}   -0.05{col 50}{space 3}0.956{col 58}{space 4}-.0306772{col 71}{space 3} .0290062
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}total            {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.3362591{col 30}{space 2} .0715003{col 41}{space 1}   -4.70{col 50}{space 3}0.000{col 58}{space 4}-.4763971{col 71}{space 3}-.1961211
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2} .1349267{col 30}{space 2} .0776016{col 41}{space 1}    1.74{col 50}{space 3}0.082{col 58}{space 4}-.0171696{col 71}{space 3} .2870231
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .1071714{col 30}{space 2} .0752368{col 41}{space 1}    1.42{col 50}{space 3}0.154{col 58}{space 4}-.0402899{col 71}{space 3} .2546328
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2}-.0005742{col 30}{space 2} .0160871{col 41}{space 1}   -0.04{col 50}{space 3}0.972{col 58}{space 4}-.0321043{col 71}{space 3} .0309559
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                          *    1-2-2020: Other temples, Guandi temples and Mazu temples_Urban vs village temples ;
. spregress chcandabs20dk lnurbanmazuden lnargimazuden lnguanden lnothertempdenv1
>                               lnchurchden 
>                                   popden_1520 
>                               child_1520 old_1520 
>                                   allcollege_1520 
>                                   inc_avg_1417 Price_unit_mean_2014_2017 
>                                   hotel_num_2018                                          
>                                   city indtn, 
>                                   ml   
>                                   ivarlag(Wd: lnurbanmazuden lnargimazuden lnguanden lnothertempdenv1) ;
{res}{txt}{col 3}(888 observations)
{col 3}(888 observations (places) used)
{col 3}(weighting matrix defines 888 places)
{res}{txt}
Optimizing unconcentrated log likelihood:

Iteration 0:{space 3}log likelihood = {res: 534.98182}  
Iteration 1:{space 3}log likelihood = {res: 534.98182}  
{res}
{txt}Spatial autoregressive model{col 49}Number of obs{col 67}= {res}       888
{txt}Maximum likelihood estimates{col 49}Wald chi2({res}18{txt}){col 67}= {res}    401.66
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} 534.98182{txt}{col 49}Pseudo R2{col 67}= {res}    0.3114

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           chcandabs20dk{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}chcandabs20dk            {txt}{c |}
{space 10}lnurbanmazuden {c |}{col 26}{res}{space 2}-.0165072{col 38}{space 2} .0145365{col 49}{space 1}   -1.14{col 58}{space 3}0.256{col 66}{space 4}-.0449982{col 79}{space 3} .0119838
{txt}{space 11}lnargimazuden {c |}{col 26}{res}{space 2}-.0402455{col 38}{space 2} .0130627{col 49}{space 1}   -3.08{col 58}{space 3}0.002{col 66}{space 4} -.065848{col 79}{space 3} -.014643
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} -.015028{col 38}{space 2} .0114278{col 49}{space 1}   -1.32{col 58}{space 3}0.188{col 66}{space 4}-.0374261{col 79}{space 3} .0073702
{txt}{space 8}lnothertempdenv1 {c |}{col 26}{res}{space 2} -.003819{col 38}{space 2}  .004936{col 49}{space 1}   -0.77{col 58}{space 3}0.439{col 66}{space 4}-.0134933{col 79}{space 3} .0058554
{txt}{space 13}lnchurchden {c |}{col 26}{res}{space 2} .0089898{col 38}{space 2} .0049013{col 49}{space 1}    1.83{col 58}{space 3}0.067{col 66}{space 4}-.0006166{col 79}{space 3} .0185961
{txt}{space 13}popden_1520 {c |}{col 26}{res}{space 2} 4.97e-07{col 38}{space 2} 5.20e-07{col 49}{space 1}    0.96{col 58}{space 3}0.339{col 66}{space 4}-5.21e-07{col 79}{space 3} 1.52e-06
{txt}{space 14}child_1520 {c |}{col 26}{res}{space 2} 1.150818{col 38}{space 2} .5939185{col 49}{space 1}    1.94{col 58}{space 3}0.053{col 66}{space 4}-.0132409{col 79}{space 3} 2.314877
{txt}{space 16}old_1520 {c |}{col 26}{res}{space 2} .5707451{col 38}{space 2} .1511286{col 49}{space 1}    3.78{col 58}{space 3}0.000{col 66}{space 4} .2745385{col 79}{space 3} .8669516
{txt}{space 9}allcollege_1520 {c |}{col 26}{res}{space 2} 1.004075{col 38}{space 2} .0951198{col 49}{space 1}   10.56{col 58}{space 3}0.000{col 66}{space 4} .8176435{col 79}{space 3} 1.190506
{txt}{space 12}inc_avg_1417 {c |}{col 26}{res}{space 2}-.0001271{col 38}{space 2} .0000343{col 49}{space 1}   -3.71{col 58}{space 3}0.000{col 66}{space 4}-.0001943{col 79}{space 3}-.0000599
{txt}Price_unit_mean_201~2017 {c |}{col 26}{res}{space 2} .0000754{col 38}{space 2} .0005395{col 49}{space 1}    0.14{col 58}{space 3}0.889{col 66}{space 4} -.000982{col 79}{space 3} .0011327
{txt}{space 10}hotel_num_2018 {c |}{col 26}{res}{space 2}-.0093333{col 38}{space 2} .0039725{col 49}{space 1}   -2.35{col 58}{space 3}0.019{col 66}{space 4}-.0171193{col 79}{space 3}-.0015472
{txt}{space 20}city {c |}{col 26}{res}{space 2} .0404051{col 38}{space 2} .0184604{col 49}{space 1}    2.19{col 58}{space 3}0.029{col 66}{space 4} .0042234{col 79}{space 3} .0765869
{txt}{space 19}indtn {c |}{col 26}{res}{space 2} .1231542{col 38}{space 2} .0411475{col 49}{space 1}    2.99{col 58}{space 3}0.003{col 66}{space 4} .0425066{col 79}{space 3} .2038018
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-.6710697{col 38}{space 2}  .047975{col 49}{space 1}  -13.99{col 58}{space 3}0.000{col 66}{space 4} -.765099{col 79}{space 3}-.5770404
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Wd                       {txt}{c |}
{space 10}lnurbanmazuden {c |}{col 26}{res}{space 2} -.602745{col 38}{space 2} .1558092{col 49}{space 1}   -3.87{col 58}{space 3}0.000{col 66}{space 4}-.9081253{col 79}{space 3}-.2973646
{txt}{space 11}lnargimazuden {c |}{col 26}{res}{space 2} .1604955{col 38}{space 2}  .169774{col 49}{space 1}    0.95{col 58}{space 3}0.344{col 66}{space 4}-.1722555{col 79}{space 3} .4932464
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .0375971{col 38}{space 2} .1627884{col 49}{space 1}    0.23{col 58}{space 3}0.817{col 66}{space 4}-.2814623{col 79}{space 3} .3566564
{txt}{space 8}lnothertempdenv1 {c |}{col 26}{res}{space 2}-.0421056{col 38}{space 2} .0344752{col 49}{space 1}   -1.22{col 58}{space 3}0.222{col 66}{space 4}-.1096758{col 79}{space 3} .0254645
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.chcandabs20dk){c |}{col 26}{res}{space 2} .0175484{col 38}{space 2} .0008328{col 66}{space 4} .0159898{col 79}{space 3}  .019259
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Wald test of spatial terms:{col 38}chi2({res}4{txt}) = {res}21.80   {col 59}{txt}Prob > chi2 = {res}0.0002
{txt}
{com}. estat impact lnurbanmazuden lnargimazuden lnguanden lnothertempdenv1 ;
{res}
{txt}progress{col 12}:{txt} 25% {txt} 50% {txt} 75% {txt}100% 

Average impacts{col 49}Number of obs{col 67}={col 69}{res}       888

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-Method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}direct           {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.0165072{col 30}{space 2} .0145365{col 41}{space 1}   -1.14{col 50}{space 3}0.256{col 58}{space 4}-.0449982{col 71}{space 3} .0119838
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2}-.0402455{col 30}{space 2} .0130627{col 41}{space 1}   -3.08{col 50}{space 3}0.002{col 58}{space 4} -.065848{col 71}{space 3} -.014643
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} -.015028{col 30}{space 2} .0114278{col 41}{space 1}   -1.32{col 50}{space 3}0.188{col 58}{space 4}-.0374261{col 71}{space 3} .0073702
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2} -.003819{col 30}{space 2}  .004936{col 41}{space 1}   -0.77{col 50}{space 3}0.439{col 58}{space 4}-.0134933{col 71}{space 3} .0058554
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}indirect         {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.2132633{col 30}{space 2} .0551284{col 41}{space 1}   -3.87{col 50}{space 3}0.000{col 58}{space 4} -.321313{col 71}{space 3}-.1052135
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2} .0567865{col 30}{space 2} .0600694{col 41}{space 1}    0.95{col 50}{space 3}0.344{col 58}{space 4}-.0609474{col 71}{space 3} .1745205
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0133026{col 30}{space 2} .0575978{col 41}{space 1}    0.23{col 50}{space 3}0.817{col 58}{space 4} -.099587{col 71}{space 3} .1261922
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2}-.0148978{col 30}{space 2}  .012198{col 41}{space 1}   -1.22{col 50}{space 3}0.222{col 58}{space 4}-.0388055{col 71}{space 3} .0090098
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}total            {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.2297705{col 30}{space 2} .0572503{col 41}{space 1}   -4.01{col 50}{space 3}0.000{col 58}{space 4}-.3419789{col 71}{space 3} -.117562
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2}  .016541{col 30}{space 2}  .062151{col 41}{space 1}    0.27{col 50}{space 3}0.790{col 58}{space 4}-.1052726{col 71}{space 3} .1383546
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2}-.0017254{col 30}{space 2} .0602354{col 41}{space 1}   -0.03{col 50}{space 3}0.977{col 58}{space 4}-.1197846{col 71}{space 3} .1163339
{txt}lnothertempdenv1 {c |}{col 18}{res}{space 2}-.0187168{col 30}{space 2} .0128817{col 41}{space 1}   -1.45{col 50}{space 3}0.146{col 58}{space 4}-.0439643{col 71}{space 3} .0065308
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ** We run the four regression commands below together to do another  ** ;
. **   check following the suggestion provided by the reviewer in the  ** ;
. **   2nd round.                                                                                                  ** ;
. ** Temple types: Mazu, Guandi, Yiguandao and the others              ;
. *    2-1-2018: Mazu, Guandi, Yiguandao temples and Other temples ;
. spregress chcandabs18dk lnmazuden lnguanden lnyiguanden lnothertempdenv2 
>                                     lnchurchden  
>                                         popden_1418   
>                                     child_1418 old_1418  
>                                         allcollege_1418  
>                                         inc_avg_1417 Price_unit_mean_2014_2017  
>                                         hotel_num_2018  
>                                         city indtn,
>                                                 ml   
>                                             ivarlag(Wd: lnmazuden lnguanden lnyiguanden lnothertempdenv2) ;
{res}{txt}{col 3}(888 observations)
{col 3}(888 observations (places) used)
{col 3}(weighting matrix defines 888 places)
{res}{txt}
Optimizing unconcentrated log likelihood:

Iteration 0:{space 3}log likelihood = {res: 327.95249}  
Iteration 1:{space 3}log likelihood = {res: 327.95249}  (backed up)
{res}
{txt}Spatial autoregressive model{col 49}Number of obs{col 67}= {res}       888
{txt}Maximum likelihood estimates{col 49}Wald chi2({res}18{txt}){col 67}= {res}    685.91
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} 327.95249{txt}{col 49}Pseudo R2{col 67}= {res}    0.4358

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           chcandabs18dk{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}chcandabs18dk            {txt}{c |}
{space 15}lnmazuden {c |}{col 26}{res}{space 2}-.0180687{col 38}{space 2} .0124593{col 49}{space 1}   -1.45{col 58}{space 3}0.147{col 66}{space 4}-.0424885{col 79}{space 3} .0063511
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .0030969{col 38}{space 2} .0144594{col 49}{space 1}    0.21{col 58}{space 3}0.830{col 66}{space 4}-.0252431{col 79}{space 3} .0314369
{txt}{space 13}lnyiguanden {c |}{col 26}{res}{space 2}-.0228547{col 38}{space 2} .0519538{col 49}{space 1}   -0.44{col 58}{space 3}0.660{col 66}{space 4}-.1246823{col 79}{space 3} .0789729
{txt}{space 8}lnothertempdenv2 {c |}{col 26}{res}{space 2} .0028102{col 38}{space 2} .0062259{col 49}{space 1}    0.45{col 58}{space 3}0.652{col 66}{space 4}-.0093922{col 79}{space 3} .0150127
{txt}{space 13}lnchurchden {c |}{col 26}{res}{space 2}-.0011829{col 38}{space 2} .0062043{col 49}{space 1}   -0.19{col 58}{space 3}0.849{col 66}{space 4}-.0133431{col 79}{space 3} .0109772
{txt}{space 13}popden_1418 {c |}{col 26}{res}{space 2} 7.49e-07{col 38}{space 2} 6.53e-07{col 49}{space 1}    1.15{col 58}{space 3}0.251{col 66}{space 4}-5.31e-07{col 79}{space 3} 2.03e-06
{txt}{space 14}child_1418 {c |}{col 26}{res}{space 2}-2.716727{col 38}{space 2} .7209652{col 49}{space 1}   -3.77{col 58}{space 3}0.000{col 66}{space 4}-4.129793{col 79}{space 3}-1.303662
{txt}{space 16}old_1418 {c |}{col 26}{res}{space 2} .9195158{col 38}{space 2} .1867714{col 49}{space 1}    4.92{col 58}{space 3}0.000{col 66}{space 4} .5534506{col 79}{space 3} 1.285581
{txt}{space 9}allcollege_1418 {c |}{col 26}{res}{space 2} 1.238312{col 38}{space 2} .1214919{col 49}{space 1}   10.19{col 58}{space 3}0.000{col 66}{space 4} 1.000192{col 79}{space 3} 1.476432
{txt}{space 12}inc_avg_1417 {c |}{col 26}{res}{space 2}-.0000605{col 38}{space 2} .0000433{col 49}{space 1}   -1.40{col 58}{space 3}0.163{col 66}{space 4}-.0001454{col 79}{space 3} .0000244
{txt}Price_unit_mean_201~2017 {c |}{col 26}{res}{space 2} .0003367{col 38}{space 2} .0006837{col 49}{space 1}    0.49{col 58}{space 3}0.622{col 66}{space 4}-.0010033{col 79}{space 3} .0016768
{txt}{space 10}hotel_num_2018 {c |}{col 26}{res}{space 2}-.0130243{col 38}{space 2} .0050218{col 49}{space 1}   -2.59{col 58}{space 3}0.009{col 66}{space 4}-.0228669{col 79}{space 3}-.0031816
{txt}{space 20}city {c |}{col 26}{res}{space 2} -.093627{col 38}{space 2} .0232985{col 49}{space 1}   -4.02{col 58}{space 3}0.000{col 66}{space 4}-.1392913{col 79}{space 3}-.0479627
{txt}{space 19}indtn {c |}{col 26}{res}{space 2}-.5173216{col 38}{space 2} .0526843{col 49}{space 1}   -9.82{col 58}{space 3}0.000{col 66}{space 4}-.6205809{col 79}{space 3}-.4140624
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-1.270959{col 38}{space 2} .0583766{col 49}{space 1}  -21.77{col 58}{space 3}0.000{col 66}{space 4}-1.385375{col 79}{space 3}-1.156543
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Wd                       {txt}{c |}
{space 15}lnmazuden {c |}{col 26}{res}{space 2}-.2926841{col 38}{space 2} .1528989{col 49}{space 1}   -1.91{col 58}{space 3}0.056{col 66}{space 4}-.5923604{col 79}{space 3} .0069921
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .2514583{col 38}{space 2} .2060297{col 49}{space 1}    1.22{col 58}{space 3}0.222{col 66}{space 4}-.1523525{col 79}{space 3} .6552692
{txt}{space 13}lnyiguanden {c |}{col 26}{res}{space 2} .0078358{col 38}{space 2} .9748127{col 49}{space 1}    0.01{col 58}{space 3}0.994{col 66}{space 4}-1.902762{col 79}{space 3} 1.918434
{txt}{space 8}lnothertempdenv2 {c |}{col 26}{res}{space 2} .0039404{col 38}{space 2} .0437598{col 49}{space 1}    0.09{col 58}{space 3}0.928{col 66}{space 4}-.0818273{col 79}{space 3} .0897081
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.chcandabs18dk){c |}{col 26}{res}{space 2} .0279732{col 38}{space 2} .0013275{col 66}{space 4} .0254886{col 79}{space 3}    .0307
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Wald test of spatial terms:{col 38}chi2({res}4{txt}) = {res}6.75    {col 59}{txt}Prob > chi2 = {res}0.1496
{txt}
{com}. estat impact lnmazuden lnguanden lnyiguanden lnothertempdenv2 ;
{res}
{txt}progress{col 12}:{txt} 25% {txt} 50% {txt} 75% {txt}100% 

Average impacts{col 49}Number of obs{col 67}={col 69}{res}       888

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-Method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}direct           {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.0180687{col 30}{space 2} .0124593{col 41}{space 1}   -1.45{col 50}{space 3}0.147{col 58}{space 4}-.0424885{col 71}{space 3} .0063511
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0030969{col 30}{space 2} .0144594{col 41}{space 1}    0.21{col 50}{space 3}0.830{col 58}{space 4}-.0252431{col 71}{space 3} .0314369
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2}-.0228547{col 30}{space 2} .0519538{col 41}{space 1}   -0.44{col 50}{space 3}0.660{col 58}{space 4}-.1246823{col 71}{space 3} .0789729
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2} .0028102{col 30}{space 2} .0062259{col 41}{space 1}    0.45{col 50}{space 3}0.652{col 58}{space 4}-.0093922{col 71}{space 3} .0150127
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}indirect         {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.1035575{col 30}{space 2} .0540987{col 41}{space 1}   -1.91{col 50}{space 3}0.056{col 58}{space 4} -.209589{col 71}{space 3}  .002474
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2}  .088971{col 30}{space 2} .0728974{col 41}{space 1}    1.22{col 50}{space 3}0.222{col 58}{space 4}-.0539054{col 71}{space 3} .2318474
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2} .0027725{col 30}{space 2} .3449083{col 41}{space 1}    0.01{col 50}{space 3}0.994{col 58}{space 4}-.6732354{col 71}{space 3} .6787803
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2} .0013942{col 30}{space 2} .0154831{col 41}{space 1}    0.09{col 50}{space 3}0.928{col 58}{space 4}-.0289521{col 71}{space 3} .0317405
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}total            {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.1216262{col 30}{space 2} .0562835{col 41}{space 1}   -2.16{col 50}{space 3}0.031{col 58}{space 4}-.2319398{col 71}{space 3}-.0113126
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0920679{col 30}{space 2} .0762252{col 41}{space 1}    1.21{col 50}{space 3}0.227{col 58}{space 4}-.0573307{col 71}{space 3} .2414666
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2}-.0200822{col 30}{space 2} .3508384{col 41}{space 1}   -0.06{col 50}{space 3}0.954{col 58}{space 4}-.7077128{col 71}{space 3} .6675484
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2} .0042045{col 30}{space 2} .0163452{col 41}{space 1}    0.26{col 50}{space 3}0.797{col 58}{space 4}-.0278315{col 71}{space 3} .0362404
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *    2-1-2020: Mazu, Guandi, Yiguandao temples and Other temples ;
. spregress chcandabs20dk lnmazuden lnguanden lnyiguanden lnothertempdenv2 
>                                                 lnchurchden
>                                             popden_1520 
>                                     child_1520 old_1520 
>                                         allcollege_1520
>                                             inc_avg_1417 Price_unit_mean_2014_2017 
>                                             hotel_num_2018      
>                                                 city indtn,
>                                                 ml   
>                                             ivarlag(Wd: lnmazuden lnguanden lnyiguanden lnothertempdenv2) ;
{res}{txt}{col 3}(888 observations)
{col 3}(888 observations (places) used)
{col 3}(weighting matrix defines 888 places)
{res}{txt}
Optimizing unconcentrated log likelihood:

Iteration 0:{space 3}log likelihood = {res: 528.54452}  
Iteration 1:{space 3}log likelihood = {res: 528.54452}  
{res}
{txt}Spatial autoregressive model{col 49}Number of obs{col 67}= {res}       888
{txt}Maximum likelihood estimates{col 49}Wald chi2({res}18{txt}){col 67}= {res}    383.10
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} 528.54452{txt}{col 49}Pseudo R2{col 67}= {res}    0.3014

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           chcandabs20dk{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}chcandabs20dk            {txt}{c |}
{space 15}lnmazuden {c |}{col 26}{res}{space 2}-.0300889{col 38}{space 2} .0099381{col 49}{space 1}   -3.03{col 58}{space 3}0.002{col 66}{space 4}-.0495672{col 79}{space 3}-.0106106
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2}-.0147815{col 38}{space 2} .0115357{col 49}{space 1}   -1.28{col 58}{space 3}0.200{col 66}{space 4} -.037391{col 79}{space 3} .0078281
{txt}{space 13}lnyiguanden {c |}{col 26}{res}{space 2} -.005498{col 38}{space 2} .0414588{col 49}{space 1}   -0.13{col 58}{space 3}0.894{col 66}{space 4}-.0867556{col 79}{space 3} .0757597
{txt}{space 8}lnothertempdenv2 {c |}{col 26}{res}{space 2}-.0031913{col 38}{space 2} .0049673{col 49}{space 1}   -0.64{col 58}{space 3}0.521{col 66}{space 4} -.012927{col 79}{space 3} .0065444
{txt}{space 13}lnchurchden {c |}{col 26}{res}{space 2} .0091019{col 38}{space 2}  .004943{col 49}{space 1}    1.84{col 58}{space 3}0.066{col 66}{space 4}-.0005862{col 79}{space 3} .0187899
{txt}{space 13}popden_1520 {c |}{col 26}{res}{space 2} 4.78e-07{col 38}{space 2} 5.24e-07{col 49}{space 1}    0.91{col 58}{space 3}0.361{col 66}{space 4}-5.49e-07{col 79}{space 3} 1.51e-06
{txt}{space 14}child_1520 {c |}{col 26}{res}{space 2} 1.173344{col 38}{space 2} .5978482{col 49}{space 1}    1.96{col 58}{space 3}0.050{col 66}{space 4} .0015833{col 79}{space 3} 2.345105
{txt}{space 16}old_1520 {c |}{col 26}{res}{space 2} .5650075{col 38}{space 2} .1519118{col 49}{space 1}    3.72{col 58}{space 3}0.000{col 66}{space 4} .2672658{col 79}{space 3} .8627491
{txt}{space 9}allcollege_1520 {c |}{col 26}{res}{space 2} 1.007052{col 38}{space 2} .0965753{col 49}{space 1}   10.43{col 58}{space 3}0.000{col 66}{space 4}  .817768{col 79}{space 3} 1.196336
{txt}{space 12}inc_avg_1417 {c |}{col 26}{res}{space 2} -.000134{col 38}{space 2} .0000345{col 49}{space 1}   -3.88{col 58}{space 3}0.000{col 66}{space 4}-.0002016{col 79}{space 3}-.0000664
{txt}Price_unit_mean_201~2017 {c |}{col 26}{res}{space 2} .0000732{col 38}{space 2} .0005469{col 49}{space 1}    0.13{col 58}{space 3}0.893{col 66}{space 4}-.0009987{col 79}{space 3} .0011452
{txt}{space 10}hotel_num_2018 {c |}{col 26}{res}{space 2}-.0094182{col 38}{space 2} .0040048{col 49}{space 1}   -2.35{col 58}{space 3}0.019{col 66}{space 4}-.0172674{col 79}{space 3} -.001569
{txt}{space 20}city {c |}{col 26}{res}{space 2} .0386583{col 38}{space 2} .0185667{col 49}{space 1}    2.08{col 58}{space 3}0.037{col 66}{space 4} .0022684{col 79}{space 3} .0750483
{txt}{space 19}indtn {c |}{col 26}{res}{space 2} .1197749{col 38}{space 2} .0414579{col 49}{space 1}    2.89{col 58}{space 3}0.004{col 66}{space 4} .0385188{col 79}{space 3}  .201031
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-.6645718{col 38}{space 2} .0482062{col 49}{space 1}  -13.79{col 58}{space 3}0.000{col 66}{space 4}-.7590543{col 79}{space 3}-.5700894
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Wd                       {txt}{c |}
{space 15}lnmazuden {c |}{col 26}{res}{space 2}-.2403387{col 38}{space 2} .1218478{col 49}{space 1}   -1.97{col 58}{space 3}0.049{col 66}{space 4}-.4791561{col 79}{space 3}-.0015213
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .0302321{col 38}{space 2} .1642523{col 49}{space 1}    0.18{col 58}{space 3}0.854{col 66}{space 4}-.2916965{col 79}{space 3} .3521606
{txt}{space 13}lnyiguanden {c |}{col 26}{res}{space 2} -.370856{col 38}{space 2} .7779819{col 49}{space 1}   -0.48{col 58}{space 3}0.634{col 66}{space 4}-1.895672{col 79}{space 3}  1.15396
{txt}{space 8}lnothertempdenv2 {c |}{col 26}{res}{space 2}-.0428359{col 38}{space 2} .0349015{col 49}{space 1}   -1.23{col 58}{space 3}0.220{col 66}{space 4}-.1112414{col 79}{space 3} .0255697
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.chcandabs20dk){c |}{col 26}{res}{space 2} .0178047{col 38}{space 2}  .000845{col 66}{space 4} .0162233{col 79}{space 3} .0195403
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Wald test of spatial terms:{col 38}chi2({res}4{txt}) = {res}10.21   {col 59}{txt}Prob > chi2 = {res}0.0370
{txt}
{com}. estat impact lnmazuden lnguanden lnyiguanden lnothertempdenv2 ;
{res}
{txt}progress{col 12}:{txt} 25% {txt} 50% {txt} 75% {txt}100% 

Average impacts{col 49}Number of obs{col 67}={col 69}{res}       888

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-Method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}direct           {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.0300889{col 30}{space 2} .0099381{col 41}{space 1}   -3.03{col 50}{space 3}0.002{col 58}{space 4}-.0495672{col 71}{space 3}-.0106106
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2}-.0147815{col 30}{space 2} .0115357{col 41}{space 1}   -1.28{col 50}{space 3}0.200{col 58}{space 4} -.037391{col 71}{space 3} .0078281
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2} -.005498{col 30}{space 2} .0414588{col 41}{space 1}   -0.13{col 50}{space 3}0.894{col 58}{space 4}-.0867556{col 71}{space 3} .0757597
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2}-.0031913{col 30}{space 2} .0049673{col 41}{space 1}   -0.64{col 50}{space 3}0.521{col 58}{space 4} -.012927{col 71}{space 3} .0065444
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}indirect         {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.0850367{col 30}{space 2} .0431122{col 41}{space 1}   -1.97{col 50}{space 3}0.049{col 58}{space 4} -.169535{col 71}{space 3}-.0005383
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0106967{col 30}{space 2} .0581158{col 41}{space 1}    0.18{col 50}{space 3}0.854{col 58}{space 4}-.1032081{col 71}{space 3} .1246015
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2}-.1312163{col 30}{space 2} .2752656{col 41}{space 1}   -0.48{col 50}{space 3}0.634{col 58}{space 4}-.6707269{col 71}{space 3} .4082943
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2}-.0151562{col 30}{space 2} .0123488{col 41}{space 1}   -1.23{col 50}{space 3}0.220{col 58}{space 4}-.0393595{col 71}{space 3} .0090471
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}total            {txt}{c |}
{space 7}lnmazuden {c |}{col 18}{res}{space 2}-.1151255{col 30}{space 2} .0448453{col 41}{space 1}   -2.57{col 50}{space 3}0.010{col 58}{space 4}-.2030207{col 71}{space 3}-.0272304
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2}-.0040847{col 30}{space 2}  .060756{col 41}{space 1}   -0.07{col 50}{space 3}0.946{col 58}{space 4}-.1231643{col 71}{space 3} .1149948
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2}-.1367143{col 30}{space 2}  .280023{col 41}{space 1}   -0.49{col 50}{space 3}0.625{col 58}{space 4}-.6855493{col 71}{space 3} .4121208
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2}-.0183475{col 30}{space 2} .0130305{col 41}{space 1}   -1.41{col 50}{space 3}0.159{col 58}{space 4}-.0438867{col 71}{space 3} .0071918
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *    2-2-2018: Other temples, Guandi, Yiguandao temples and Mazu temples_Urban vs village temples ;
. spregress chcandabs18dk lnurbanmazuden lnargimazuden lnguanden lnyiguanden lnothertempdenv2
>                                     lnchurchden  
>                                         popden_1418   
>                                     child_1418 old_1418  
>                                         allcollege_1418  
>                                         inc_avg_1417 Price_unit_mean_2014_2017  
>                                         hotel_num_2018  
>                                         city indtn,
>                                                 ml   
>                                             ivarlag(Wd: lnurbanmazuden lnargimazuden lnguanden lnyiguanden lnothertempdenv2) ;
{res}{txt}{col 3}(888 observations)
{col 3}(888 observations (places) used)
{col 3}(weighting matrix defines 888 places)
{res}{txt}
Optimizing unconcentrated log likelihood:

Iteration 0:{space 3}log likelihood = {res: 338.39752}  
Iteration 1:{space 3}log likelihood = {res: 338.39752}  (backed up)
{res}
{txt}Spatial autoregressive model{col 49}Number of obs{col 67}= {res}       888
{txt}Maximum likelihood estimates{col 49}Wald chi2({res}20{txt}){col 67}= {res}    723.37
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} 338.39752{txt}{col 49}Pseudo R2{col 67}= {res}    0.4489

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           chcandabs18dk{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}chcandabs18dk            {txt}{c |}
{space 10}lnurbanmazuden {c |}{col 26}{res}{space 2}-.0356723{col 38}{space 2} .0181599{col 49}{space 1}   -1.96{col 58}{space 3}0.049{col 66}{space 4} -.071265{col 79}{space 3}-.0000796
{txt}{space 11}lnargimazuden {c |}{col 26}{res}{space 2} -.002589{col 38}{space 2} .0163114{col 49}{space 1}   -0.16{col 58}{space 3}0.874{col 66}{space 4}-.0345588{col 79}{space 3} .0293808
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .0037596{col 38}{space 2} .0142956{col 49}{space 1}    0.26{col 58}{space 3}0.793{col 66}{space 4}-.0242594{col 79}{space 3} .0317785
{txt}{space 13}lnyiguanden {c |}{col 26}{res}{space 2}-.0143803{col 38}{space 2} .0514407{col 49}{space 1}   -0.28{col 58}{space 3}0.780{col 66}{space 4}-.1152022{col 79}{space 3} .0864417
{txt}{space 8}lnothertempdenv2 {c |}{col 26}{res}{space 2} .0006014{col 38}{space 2} .0061776{col 49}{space 1}    0.10{col 58}{space 3}0.922{col 66}{space 4}-.0115065{col 79}{space 3} .0127093
{txt}{space 13}lnchurchden {c |}{col 26}{res}{space 2}-.0003225{col 38}{space 2} .0061395{col 49}{space 1}   -0.05{col 58}{space 3}0.958{col 66}{space 4}-.0123557{col 79}{space 3} .0117106
{txt}{space 13}popden_1418 {c |}{col 26}{res}{space 2} 8.24e-07{col 38}{space 2} 6.45e-07{col 49}{space 1}    1.28{col 58}{space 3}0.202{col 66}{space 4}-4.41e-07{col 79}{space 3} 2.09e-06
{txt}{space 14}child_1418 {c |}{col 26}{res}{space 2}-2.654522{col 38}{space 2} .7134896{col 49}{space 1}   -3.72{col 58}{space 3}0.000{col 66}{space 4}-4.052936{col 79}{space 3}-1.256108
{txt}{space 16}old_1418 {c |}{col 26}{res}{space 2}  .955655{col 38}{space 2} .1848941{col 49}{space 1}    5.17{col 58}{space 3}0.000{col 66}{space 4} .5932693{col 79}{space 3} 1.318041
{txt}{space 9}allcollege_1418 {c |}{col 26}{res}{space 2} 1.223962{col 38}{space 2} .1201781{col 49}{space 1}   10.18{col 58}{space 3}0.000{col 66}{space 4} .9884169{col 79}{space 3} 1.459506
{txt}{space 12}inc_avg_1417 {c |}{col 26}{res}{space 2}  -.00005{col 38}{space 2} .0000429{col 49}{space 1}   -1.17{col 58}{space 3}0.244{col 66}{space 4}-.0001341{col 79}{space 3} .0000341
{txt}Price_unit_mean_201~2017 {c |}{col 26}{res}{space 2} .0003451{col 38}{space 2} .0006758{col 49}{space 1}    0.51{col 58}{space 3}0.610{col 66}{space 4}-.0009794{col 79}{space 3} .0016697
{txt}{space 10}hotel_num_2018 {c |}{col 26}{res}{space 2} -.012725{col 38}{space 2} .0049639{col 49}{space 1}   -2.56{col 58}{space 3}0.010{col 66}{space 4}-.0224541{col 79}{space 3}-.0029958
{txt}{space 20}city {c |}{col 26}{res}{space 2}-.0859696{col 38}{space 2} .0231048{col 49}{space 1}   -3.72{col 58}{space 3}0.000{col 66}{space 4}-.1312541{col 79}{space 3}-.0406851
{txt}{space 19}indtn {c |}{col 26}{res}{space 2} -.510044{col 38}{space 2} .0520924{col 49}{space 1}   -9.79{col 58}{space 3}0.000{col 66}{space 4}-.6121433{col 79}{space 3}-.4079448
{txt}{space 19}_cons {c |}{col 26}{res}{space 2} -1.29087{col 38}{space 2} .0578889{col 49}{space 1}  -22.30{col 58}{space 3}0.000{col 66}{space 4} -1.40433{col 79}{space 3} -1.17741
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Wd                       {txt}{c |}
{space 10}lnurbanmazuden {c |}{col 26}{res}{space 2}-.8601466{col 38}{space 2} .1992582{col 49}{space 1}   -4.32{col 58}{space 3}0.000{col 66}{space 4}-1.250685{col 79}{space 3}-.4696077
{txt}{space 11}lnargimazuden {c |}{col 26}{res}{space 2}  .378009{col 38}{space 2} .2140229{col 49}{space 1}    1.77{col 58}{space 3}0.077{col 66}{space 4}-.0414683{col 79}{space 3} .7974862
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .2831911{col 38}{space 2} .2037869{col 49}{space 1}    1.39{col 58}{space 3}0.165{col 66}{space 4}-.1162238{col 79}{space 3}  .682606
{txt}{space 13}lnyiguanden {c |}{col 26}{res}{space 2} .2337698{col 38}{space 2} .9646799{col 49}{space 1}    0.24{col 58}{space 3}0.809{col 66}{space 4}-1.656968{col 79}{space 3} 2.124508
{txt}{space 8}lnothertempdenv2 {c |}{col 26}{res}{space 2} .0004094{col 38}{space 2} .0432662{col 49}{space 1}    0.01{col 58}{space 3}0.992{col 66}{space 4}-.0843908{col 79}{space 3} .0852096
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.chcandabs18dk){c |}{col 26}{res}{space 2} .0273228{col 38}{space 2} .0012967{col 66}{space 4}  .024896{col 79}{space 3} .0299862
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Wald test of spatial terms:{col 38}chi2({res}5{txt}) = {res}26.26   {col 59}{txt}Prob > chi2 = {res}0.0001
{txt}
{com}. estat impact lnurbanmazuden lnargimazuden lnguanden lnyiguanden lnothertempdenv2 ;
{res}
{txt}progress{col 12}:{txt} 20% {txt} 40% {txt} 60% {txt} 80% {txt}100% 

Average impacts{col 49}Number of obs{col 67}={col 69}{res}       888

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-Method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}direct           {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.0356723{col 30}{space 2} .0181599{col 41}{space 1}   -1.96{col 50}{space 3}0.049{col 58}{space 4} -.071265{col 71}{space 3}-.0000796
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2} -.002589{col 30}{space 2} .0163114{col 41}{space 1}   -0.16{col 50}{space 3}0.874{col 58}{space 4}-.0345588{col 71}{space 3} .0293808
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0037596{col 30}{space 2} .0142956{col 41}{space 1}    0.26{col 50}{space 3}0.793{col 58}{space 4}-.0242594{col 71}{space 3} .0317785
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2}-.0143803{col 30}{space 2} .0514407{col 41}{space 1}   -0.28{col 50}{space 3}0.780{col 58}{space 4}-.1152022{col 71}{space 3} .0864417
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2} .0006014{col 30}{space 2} .0061776{col 41}{space 1}    0.10{col 50}{space 3}0.922{col 58}{space 4}-.0115065{col 71}{space 3} .0127093
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}indirect         {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.3043371{col 30}{space 2} .0705015{col 41}{space 1}   -4.32{col 50}{space 3}0.000{col 58}{space 4}-.4425176{col 71}{space 3}-.1661566
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2} .1337471{col 30}{space 2} .0757256{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4}-.0146723{col 71}{space 3} .2821666
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .1001987{col 30}{space 2} .0721039{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4}-.0411223{col 71}{space 3} .2415197
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2} .0827124{col 30}{space 2} .3413231{col 41}{space 1}    0.24{col 50}{space 3}0.809{col 58}{space 4}-.5862685{col 71}{space 3} .7516934
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2} .0001448{col 30}{space 2} .0153084{col 41}{space 1}    0.01{col 50}{space 3}0.992{col 58}{space 4}-.0298592{col 71}{space 3} .0301489
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}total            {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.3400094{col 30}{space 2} .0731635{col 41}{space 1}   -4.65{col 50}{space 3}0.000{col 58}{space 4}-.4834072{col 71}{space 3}-.1966115
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2} .1311582{col 30}{space 2} .0783277{col 41}{space 1}    1.67{col 50}{space 3}0.094{col 58}{space 4}-.0223614{col 71}{space 3} .2846777
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .1039583{col 30}{space 2} .0754034{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0438297{col 71}{space 3} .2517463
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2} .0683322{col 30}{space 2} .3472692{col 41}{space 1}    0.20{col 50}{space 3}0.844{col 58}{space 4} -.612303{col 71}{space 3} .7489673
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2} .0007463{col 30}{space 2} .0161834{col 41}{space 1}    0.05{col 50}{space 3}0.963{col 58}{space 4}-.0309726{col 71}{space 3} .0324651
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.                          *    2-2-2020: Other temples, Guandi, Yiguandao temples and Mazu temples_Urban vs village temples ;
. spregress chcandabs20dk lnurbanmazuden lnargimazuden lnguanden lnyiguanden lnothertempdenv2
>                               lnchurchden 
>                                   popden_1520 
>                               child_1520 old_1520 
>                                   allcollege_1520 
>                                   inc_avg_1417 Price_unit_mean_2014_2017 
>                                   hotel_num_2018                                          
>                                   city indtn, 
>                                   ml   
>                                   ivarlag(Wd: lnurbanmazuden lnargimazuden lnguanden lnyiguanden lnothertempdenv2) ;
{res}{txt}{col 3}(888 observations)
{col 3}(888 observations (places) used)
{col 3}(weighting matrix defines 888 places)
{res}{txt}
Optimizing unconcentrated log likelihood:

Iteration 0:{space 3}log likelihood = {res: 535.00947}  
Iteration 1:{space 3}log likelihood = {res: 535.00947}  (backed up)
{res}
{txt}Spatial autoregressive model{col 49}Number of obs{col 67}= {res}       888
{txt}Maximum likelihood estimates{col 49}Wald chi2({res}20{txt}){col 67}= {res}    401.74
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} 535.00947{txt}{col 49}Pseudo R2{col 67}= {res}    0.3115

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           chcandabs20dk{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}chcandabs20dk            {txt}{c |}
{space 10}lnurbanmazuden {c |}{col 26}{res}{space 2}-.0163744{col 38}{space 2} .0145604{col 49}{space 1}   -1.12{col 58}{space 3}0.261{col 66}{space 4}-.0449122{col 79}{space 3} .0121634
{txt}{space 11}lnargimazuden {c |}{col 26}{res}{space 2}-.0402731{col 38}{space 2}  .013067{col 49}{space 1}   -3.08{col 58}{space 3}0.002{col 66}{space 4}-.0658839{col 79}{space 3}-.0146623
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2}-.0150843{col 38}{space 2}  .011456{col 49}{space 1}   -1.32{col 58}{space 3}0.188{col 66}{space 4}-.0375377{col 79}{space 3} .0073691
{txt}{space 13}lnyiguanden {c |}{col 26}{res}{space 2}-.0057825{col 38}{space 2} .0412333{col 49}{space 1}   -0.14{col 58}{space 3}0.888{col 66}{space 4}-.0865983{col 79}{space 3} .0750333
{txt}{space 8}lnothertempdenv2 {c |}{col 26}{res}{space 2}-.0038216{col 38}{space 2} .0049509{col 49}{space 1}   -0.77{col 58}{space 3}0.440{col 66}{space 4}-.0135253{col 79}{space 3}  .005882
{txt}{space 13}lnchurchden {c |}{col 26}{res}{space 2} .0090916{col 38}{space 2} .0049133{col 49}{space 1}    1.85{col 58}{space 3}0.064{col 66}{space 4}-.0005384{col 79}{space 3} .0187215
{txt}{space 13}popden_1520 {c |}{col 26}{res}{space 2} 5.03e-07{col 38}{space 2} 5.20e-07{col 49}{space 1}    0.97{col 58}{space 3}0.333{col 66}{space 4}-5.17e-07{col 79}{space 3} 1.52e-06
{txt}{space 14}child_1520 {c |}{col 26}{res}{space 2} 1.156122{col 38}{space 2} .5944531{col 49}{space 1}    1.94{col 58}{space 3}0.052{col 66}{space 4}-.0089851{col 79}{space 3} 2.321228
{txt}{space 16}old_1520 {c |}{col 26}{res}{space 2} .5704093{col 38}{space 2}  .151085{col 49}{space 1}    3.78{col 58}{space 3}0.000{col 66}{space 4} .2742882{col 79}{space 3} .8665304
{txt}{space 9}allcollege_1520 {c |}{col 26}{res}{space 2} 1.007866{col 38}{space 2} .0959929{col 49}{space 1}   10.50{col 58}{space 3}0.000{col 66}{space 4} .8197238{col 79}{space 3} 1.196009
{txt}{space 12}inc_avg_1417 {c |}{col 26}{res}{space 2}-.0001271{col 38}{space 2} .0000343{col 49}{space 1}   -3.71{col 58}{space 3}0.000{col 66}{space 4}-.0001944{col 79}{space 3}-.0000599
{txt}Price_unit_mean_201~2017 {c |}{col 26}{res}{space 2}  .000055{col 38}{space 2}  .000543{col 49}{space 1}    0.10{col 58}{space 3}0.919{col 66}{space 4}-.0010094{col 79}{space 3} .0011193
{txt}{space 10}hotel_num_2018 {c |}{col 26}{res}{space 2}-.0093885{col 38}{space 2} .0039764{col 49}{space 1}   -2.36{col 58}{space 3}0.018{col 66}{space 4}-.0171821{col 79}{space 3}-.0015949
{txt}{space 20}city {c |}{col 26}{res}{space 2} .0407881{col 38}{space 2}  .018496{col 49}{space 1}    2.21{col 58}{space 3}0.027{col 66}{space 4} .0045367{col 79}{space 3} .0770395
{txt}{space 19}indtn {c |}{col 26}{res}{space 2} .1226573{col 38}{space 2} .0411742{col 49}{space 1}    2.98{col 58}{space 3}0.003{col 66}{space 4} .0419574{col 79}{space 3} .2033572
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}-.6714766{col 38}{space 2} .0480279{col 49}{space 1}  -13.98{col 58}{space 3}0.000{col 66}{space 4}-.7656095{col 79}{space 3}-.5773437
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}Wd                       {txt}{c |}
{space 10}lnurbanmazuden {c |}{col 26}{res}{space 2} -.594255{col 38}{space 2} .1595332{col 49}{space 1}   -3.72{col 58}{space 3}0.000{col 66}{space 4}-.9069343{col 79}{space 3}-.2815756
{txt}{space 11}lnargimazuden {c |}{col 26}{res}{space 2} .1668168{col 38}{space 2} .1714479{col 49}{space 1}    0.97{col 58}{space 3}0.331{col 66}{space 4}-.1692149{col 79}{space 3} .5028485
{txt}{space 15}lnguanden {c |}{col 26}{res}{space 2} .0383103{col 38}{space 2} .1631958{col 49}{space 1}    0.23{col 58}{space 3}0.814{col 66}{space 4}-.2815477{col 79}{space 3} .3581683
{txt}{space 13}lnyiguanden {c |}{col 26}{res}{space 2}-.2506994{col 38}{space 2} .7733346{col 49}{space 1}   -0.32{col 58}{space 3}0.746{col 66}{space 4}-1.766407{col 79}{space 3} 1.265008
{txt}{space 8}lnothertempdenv2 {c |}{col 26}{res}{space 2}-.0426592{col 38}{space 2} .0346624{col 49}{space 1}   -1.23{col 58}{space 3}0.218{col 66}{space 4}-.1105963{col 79}{space 3} .0252779
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.chcandabs20dk){c |}{col 26}{res}{space 2} .0175473{col 38}{space 2} .0008328{col 66}{space 4} .0159888{col 79}{space 3} .0192578
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Wald test of spatial terms:{col 38}chi2({res}5{txt}) = {res}21.87   {col 59}{txt}Prob > chi2 = {res}0.0006
{txt}
{com}. estat impact lnurbanmazuden lnargimazuden lnguanden lnyiguanden lnothertempdenv2 ;
{res}
{txt}progress{col 12}:{txt} 20% {txt} 40% {txt} 60% {txt} 80% {txt}100% 

Average impacts{col 49}Number of obs{col 67}={col 69}{res}       888

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-Method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}direct           {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.0163744{col 30}{space 2} .0145604{col 41}{space 1}   -1.12{col 50}{space 3}0.261{col 58}{space 4}-.0449122{col 71}{space 3} .0121634
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2}-.0402731{col 30}{space 2}  .013067{col 41}{space 1}   -3.08{col 50}{space 3}0.002{col 58}{space 4}-.0658839{col 71}{space 3}-.0146623
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2}-.0150843{col 30}{space 2}  .011456{col 41}{space 1}   -1.32{col 50}{space 3}0.188{col 58}{space 4}-.0375377{col 71}{space 3} .0073691
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2}-.0057825{col 30}{space 2} .0412333{col 41}{space 1}   -0.14{col 50}{space 3}0.888{col 58}{space 4}-.0865983{col 71}{space 3} .0750333
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2}-.0038216{col 30}{space 2} .0049509{col 41}{space 1}   -0.77{col 50}{space 3}0.440{col 58}{space 4}-.0135253{col 71}{space 3}  .005882
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}indirect         {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.2102593{col 30}{space 2}  .056446{col 41}{space 1}   -3.72{col 50}{space 3}0.000{col 58}{space 4}-.3208915{col 71}{space 3}-.0996271
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2} .0590231{col 30}{space 2} .0606617{col 41}{space 1}    0.97{col 50}{space 3}0.331{col 58}{space 4}-.0598716{col 71}{space 3} .1779179
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2} .0135549{col 30}{space 2}  .057742{col 41}{space 1}    0.23{col 50}{space 3}0.814{col 58}{space 4}-.0996172{col 71}{space 3} .1267271
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2}-.0887025{col 30}{space 2} .2736213{col 41}{space 1}   -0.32{col 50}{space 3}0.746{col 58}{space 4}-.6249903{col 71}{space 3} .4475854
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2}-.0150937{col 30}{space 2} .0122643{col 41}{space 1}   -1.23{col 50}{space 3}0.218{col 58}{space 4}-.0391312{col 71}{space 3} .0089438
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}total            {txt}{c |}
{space 2}lnurbanmazuden {c |}{col 18}{res}{space 2}-.2266338{col 30}{space 2} .0585793{col 41}{space 1}   -3.87{col 50}{space 3}0.000{col 58}{space 4}-.3414471{col 71}{space 3}-.1118204
{txt}{space 3}lnargimazuden {c |}{col 18}{res}{space 2}   .01875{col 30}{space 2} .0627378{col 41}{space 1}    0.30{col 50}{space 3}0.765{col 58}{space 4}-.1042138{col 71}{space 3} .1417139
{txt}{space 7}lnguanden {c |}{col 18}{res}{space 2}-.0015293{col 30}{space 2} .0603713{col 41}{space 1}   -0.03{col 50}{space 3}0.980{col 58}{space 4}-.1198549{col 71}{space 3} .1167962
{txt}{space 5}lnyiguanden {c |}{col 18}{res}{space 2} -.094485{col 30}{space 2} .2784116{col 41}{space 1}   -0.34{col 50}{space 3}0.734{col 58}{space 4}-.6401618{col 71}{space 3} .4511918
{txt}lnothertempdenv2 {c |}{col 18}{res}{space 2}-.0189153{col 30}{space 2} .0129589{col 41}{space 1}   -1.46{col 50}{space 3}0.144{col 58}{space 4}-.0443143{col 71}{space 3} .0064837
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. log close ;
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\data\Vote20-KH_log_v60_ForReleaseR2-FPA.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}20 Nov 2023, 18:21:51
{txt}{.-}
{smcl}
{txt}{sf}{ul off}